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README.md ADDED
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+ ---
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+ library_name: peft
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+ license: other
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+ base_model: unsloth/Llama-3.2-3B-Instruct
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+ tags:
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+ - llama-factory
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+ - lora
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+ - unsloth
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+ - generated_from_trainer
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+ model-index:
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+ - name: llm3br256
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # llm3br256
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+
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+ This model is a fine-tuned version of [meta-llama/Llama-3.2-3B-Instruct](https://huggingface.co/meta-llama/Llama-3.2-3B-Instruct) on the centime dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0123
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 0.0001
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+ - train_batch_size: 4
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+ - eval_batch_size: 4
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+ - seed: 42
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+ - gradient_accumulation_steps: 8
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+ - total_train_batch_size: 32
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+ - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: cosine
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+ - lr_scheduler_warmup_ratio: 0.1
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+ - num_epochs: 5.0
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:------:|:----:|:---------------:|
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+ | 0.0612 | 0.0449 | 5 | 0.0560 |
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+ | 0.0411 | 0.0898 | 10 | 0.0357 |
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+ | 0.0353 | 0.1347 | 15 | 0.0301 |
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+ | 0.0286 | 0.1796 | 20 | 0.0264 |
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+ | 0.0282 | 0.2245 | 25 | 0.0239 |
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+ | 0.0223 | 0.2694 | 30 | 0.0224 |
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+ | 0.0242 | 0.3143 | 35 | 0.0209 |
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+ | 0.0211 | 0.3591 | 40 | 0.0203 |
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+ | 0.0178 | 0.4040 | 45 | 0.0201 |
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+ | 0.0206 | 0.4489 | 50 | 0.0196 |
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+ | 0.0196 | 0.4938 | 55 | 0.0193 |
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+ | 0.0173 | 0.5387 | 60 | 0.0193 |
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+ | 0.0184 | 0.5836 | 65 | 0.0193 |
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+ | 0.0194 | 0.6285 | 70 | 0.0191 |
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+ | 0.0182 | 0.6734 | 75 | 0.0185 |
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+ | 0.0169 | 0.7183 | 80 | 0.0183 |
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+ | 0.0176 | 0.7632 | 85 | 0.0178 |
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+ | 0.0158 | 0.8081 | 90 | 0.0176 |
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+ | 0.02 | 0.8530 | 95 | 0.0172 |
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+ | 0.0165 | 0.8979 | 100 | 0.0173 |
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+ | 0.0181 | 0.9428 | 105 | 0.0168 |
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+ | 0.0176 | 0.9877 | 110 | 0.0168 |
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+ | 0.0184 | 1.0348 | 115 | 0.0183 |
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+ | 0.0162 | 1.0797 | 120 | 0.0179 |
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+ | 0.017 | 1.1246 | 125 | 0.0168 |
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+ | 0.0143 | 1.1695 | 130 | 0.0167 |
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+ | 0.0177 | 1.2144 | 135 | 0.0166 |
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+ | 0.0138 | 1.2593 | 140 | 0.0161 |
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+ | 0.0149 | 1.3042 | 145 | 0.0157 |
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+ | 0.0162 | 1.3490 | 150 | 0.0160 |
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+ | 0.0148 | 1.3939 | 155 | 0.0156 |
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+ | 0.0168 | 1.4388 | 160 | 0.0154 |
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+ | 0.0148 | 1.4837 | 165 | 0.0153 |
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+ | 0.0146 | 1.5286 | 170 | 0.0154 |
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+ | 0.0137 | 1.5735 | 175 | 0.0150 |
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+ | 0.0144 | 1.6184 | 180 | 0.0150 |
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+ | 0.0129 | 1.6633 | 185 | 0.0148 |
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+ | 0.0139 | 1.7082 | 190 | 0.0145 |
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+ | 0.013 | 1.7531 | 195 | 0.0145 |
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+ | 0.013 | 1.7980 | 200 | 0.0144 |
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+ | 0.0124 | 1.8429 | 205 | 0.0144 |
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+ | 0.0135 | 1.8878 | 210 | 0.0143 |
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+ | 0.0128 | 1.9327 | 215 | 0.0147 |
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+ | 0.0149 | 1.9776 | 220 | 0.0143 |
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+ | 0.0138 | 2.0247 | 225 | 0.0144 |
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+ | 0.0127 | 2.0696 | 230 | 0.0143 |
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+ | 0.0116 | 2.1145 | 235 | 0.0142 |
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+ | 0.0128 | 2.1594 | 240 | 0.0143 |
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+ | 0.0145 | 2.2043 | 245 | 0.0141 |
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+ | 0.0147 | 2.2492 | 250 | 0.0139 |
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+ | 0.0114 | 2.2941 | 255 | 0.0139 |
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+ | 0.0114 | 2.3389 | 260 | 0.0139 |
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+ | 0.0112 | 2.3838 | 265 | 0.0137 |
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+ | 0.0105 | 2.4287 | 270 | 0.0138 |
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+ | 0.0129 | 2.4736 | 275 | 0.0136 |
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+ | 0.014 | 2.5185 | 280 | 0.0135 |
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+ | 0.0124 | 2.5634 | 285 | 0.0136 |
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+ | 0.0128 | 2.6083 | 290 | 0.0133 |
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+ | 0.0106 | 2.6532 | 295 | 0.0129 |
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+ | 0.0099 | 2.6981 | 300 | 0.0129 |
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+ | 0.0111 | 2.7430 | 305 | 0.0129 |
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+ | 0.0129 | 2.7879 | 310 | 0.0129 |
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+ | 0.0088 | 2.8328 | 315 | 0.0129 |
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+ | 0.0092 | 2.8777 | 320 | 0.0130 |
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+ | 0.0086 | 2.9226 | 325 | 0.0129 |
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+ | 0.0132 | 2.9675 | 330 | 0.0126 |
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+ | 0.0126 | 3.0146 | 335 | 0.0130 |
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+ | 0.0117 | 3.0595 | 340 | 0.0133 |
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+ | 0.0102 | 3.1044 | 345 | 0.0132 |
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+ | 0.0074 | 3.1493 | 350 | 0.0132 |
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+ | 0.0105 | 3.1942 | 355 | 0.0129 |
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+ | 0.0117 | 3.2391 | 360 | 0.0129 |
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+ | 0.0107 | 3.2840 | 365 | 0.0127 |
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+ | 0.0098 | 3.3288 | 370 | 0.0128 |
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+ | 0.0092 | 3.3737 | 375 | 0.0127 |
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+ | 0.0114 | 3.4186 | 380 | 0.0126 |
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+ | 0.0118 | 3.4635 | 385 | 0.0125 |
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+ | 0.0108 | 3.5084 | 390 | 0.0123 |
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+ | 0.0092 | 3.5533 | 395 | 0.0123 |
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+ | 0.0085 | 3.5982 | 400 | 0.0123 |
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+ | 0.0088 | 3.6431 | 405 | 0.0126 |
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+ | 0.0095 | 3.6880 | 410 | 0.0124 |
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+ | 0.0072 | 3.7329 | 415 | 0.0124 |
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+ | 0.0105 | 3.7778 | 420 | 0.0123 |
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+ | 0.0115 | 3.8227 | 425 | 0.0122 |
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+ | 0.007 | 3.8676 | 430 | 0.0121 |
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+ | 0.0112 | 3.9125 | 435 | 0.0121 |
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+ | 0.0103 | 3.9574 | 440 | 0.0121 |
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+ | 0.0162 | 4.0045 | 445 | 0.0122 |
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+ | 0.0079 | 4.0494 | 450 | 0.0125 |
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+ | 0.0102 | 4.0943 | 455 | 0.0126 |
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+ | 0.0087 | 4.1392 | 460 | 0.0126 |
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+ | 0.0107 | 4.1841 | 465 | 0.0126 |
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+ | 0.0105 | 4.2290 | 470 | 0.0125 |
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+ | 0.0089 | 4.2738 | 475 | 0.0124 |
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+ | 0.0061 | 4.3187 | 480 | 0.0125 |
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+ | 0.0074 | 4.3636 | 485 | 0.0126 |
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+ | 0.008 | 4.4085 | 490 | 0.0126 |
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+ | 0.0092 | 4.4534 | 495 | 0.0125 |
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+ | 0.0092 | 4.4983 | 500 | 0.0125 |
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+ | 0.0061 | 4.5432 | 505 | 0.0124 |
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+ | 0.0089 | 4.5881 | 510 | 0.0124 |
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+ | 0.01 | 4.6330 | 515 | 0.0124 |
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+ | 0.0081 | 4.6779 | 520 | 0.0124 |
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+ | 0.0072 | 4.7228 | 525 | 0.0124 |
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+ | 0.0078 | 4.7677 | 530 | 0.0124 |
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+ | 0.009 | 4.8126 | 535 | 0.0124 |
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+ | 0.0106 | 4.8575 | 540 | 0.0124 |
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+ | 0.0079 | 4.9024 | 545 | 0.0124 |
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+ | 0.0082 | 4.9473 | 550 | 0.0124 |
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+ | 0.0082 | 4.9921 | 555 | 0.0124 |
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+
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+
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+ ### Framework versions
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+
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+ - PEFT 0.12.0
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+ - Transformers 4.46.1
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+ - Pytorch 2.4.0+cu121
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+ - Datasets 3.1.0
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+ - Tokenizers 0.20.3
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+ "inference_mode": true,
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+ "init_lora_weights": true,
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+ "layer_replication": null,
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+ "layers_pattern": null,
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+ "layers_to_transform": null,
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+ "loftq_config": {},
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+ "lora_alpha": 256,
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+ "lora_dropout": 0.0,
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+ "megatron_config": null,
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+ "megatron_core": "megatron.core",
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+ "task_type": "CAUSAL_LM",
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+ "use_dora": false,
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+ "use_rslora": false
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+ }
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+ ---
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+ base_model: unsloth/Llama-3.2-3B-Instruct
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+ library_name: peft
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+ ---
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+
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+ # Model Card for Model ID
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+
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+ <!-- Provide a quick summary of what the model is/does. -->
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+
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+
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+
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+ ## Model Details
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+
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+ ### Model Description
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+
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+ <!-- Provide a longer summary of what this model is. -->
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+
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+
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+
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+ - **Developed by:** [More Information Needed]
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+ - **Funded by [optional]:** [More Information Needed]
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+ - **Shared by [optional]:** [More Information Needed]
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+ - **Model type:** [More Information Needed]
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+ - **Language(s) (NLP):** [More Information Needed]
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+ - **License:** [More Information Needed]
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+ - **Finetuned from model [optional]:** [More Information Needed]
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+
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+ ### Model Sources [optional]
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+
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+ <!-- Provide the basic links for the model. -->
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+
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+ - **Repository:** [More Information Needed]
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+ - **Paper [optional]:** [More Information Needed]
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+ - **Demo [optional]:** [More Information Needed]
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+
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+ ## Uses
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+
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+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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+
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+ ### Direct Use
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+
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+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
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+
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+ [More Information Needed]
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+
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+ ### Downstream Use [optional]
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+
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+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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+
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+ [More Information Needed]
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+
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+ ### Out-of-Scope Use
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+
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+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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+
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+ [More Information Needed]
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+
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+ ## Bias, Risks, and Limitations
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+
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+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
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+
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+ [More Information Needed]
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+
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+ ### Recommendations
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+
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+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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+
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+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
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+
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+ ## How to Get Started with the Model
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+
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+ Use the code below to get started with the model.
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+
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+ [More Information Needed]
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+
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+ ## Training Details
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+
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+ ### Training Data
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+
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+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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+
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+ [More Information Needed]
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+
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+ ### Training Procedure
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+
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+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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+
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+ #### Preprocessing [optional]
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+
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+ [More Information Needed]
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+
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+
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+ #### Training Hyperparameters
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+
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+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
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+
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+ #### Speeds, Sizes, Times [optional]
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+
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+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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+
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+ [More Information Needed]
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+
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+ ## Evaluation
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+
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+ <!-- This section describes the evaluation protocols and provides the results. -->
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+
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+ ### Testing Data, Factors & Metrics
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+
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+ #### Testing Data
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+
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+ <!-- This should link to a Dataset Card if possible. -->
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+
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+ [More Information Needed]
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+
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+ #### Factors
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+
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+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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+
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+ [More Information Needed]
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+
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+ #### Metrics
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+
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+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
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+
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+ [More Information Needed]
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+
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+ ### Results
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+
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+ [More Information Needed]
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+
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+ #### Summary
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+
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+
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+
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+ ## Model Examination [optional]
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+
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+ <!-- Relevant interpretability work for the model goes here -->
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+
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+ [More Information Needed]
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+
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+ ## Environmental Impact
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+
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+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
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+
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+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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+
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+ - **Hardware Type:** [More Information Needed]
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+ - **Hours used:** [More Information Needed]
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+ - **Cloud Provider:** [More Information Needed]
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+ - **Compute Region:** [More Information Needed]
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+ - **Carbon Emitted:** [More Information Needed]
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+
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+ ## Technical Specifications [optional]
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+
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+ ### Model Architecture and Objective
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+
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+ [More Information Needed]
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+
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+ ### Compute Infrastructure
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+
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+ [More Information Needed]
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+
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+ #### Hardware
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+
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+ [More Information Needed]
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+
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+ #### Software
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+
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+ [More Information Needed]
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+
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+ ## Citation [optional]
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+
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+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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+
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+ **BibTeX:**
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+
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+ [More Information Needed]
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+
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+ **APA:**
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+
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+ [More Information Needed]
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+
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+ ## Glossary [optional]
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+
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+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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+
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+ [More Information Needed]
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+
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+ ## More Information [optional]
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+
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+ [More Information Needed]
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+
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+ ## Model Card Authors [optional]
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+
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+ [More Information Needed]
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+
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+ ## Model Card Contact
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+
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+ [More Information Needed]
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+ ### Framework versions
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+
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+ - PEFT 0.12.0
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+ "content": "<|reserved_special_token_208|>",
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+ "special": true
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+ },
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+ "128217": {
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+ "content": "<|reserved_special_token_209|>",
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+ "special": true
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+ },
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+ "128218": {
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+ "content": "<|reserved_special_token_210|>",
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+ "special": true
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+ },
1755
+ "128219": {
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+ "content": "<|reserved_special_token_211|>",
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+ "lstrip": false,
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+ "normalized": false,
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+ "rstrip": false,
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+ "single_word": false,
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+ "special": true
1762
+ },
1763
+ "128220": {
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+ "content": "<|reserved_special_token_212|>",
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+ "lstrip": false,
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+ "normalized": false,
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+ "single_word": false,
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+ "special": true
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+ },
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+ "128221": {
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+ "content": "<|reserved_special_token_213|>",
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+ "single_word": false,
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+ "special": true
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+ },
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+ "128222": {
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+ "content": "<|reserved_special_token_214|>",
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+ "special": true
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+ },
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+ "128223": {
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+ "single_word": false,
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+ "special": true
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+ },
1795
+ "128224": {
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+ "content": "<|reserved_special_token_216|>",
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+ "lstrip": false,
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+ "normalized": false,
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+ "rstrip": false,
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+ "single_word": false,
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+ "special": true
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+ },
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+ "128225": {
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+ "content": "<|reserved_special_token_217|>",
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+ "lstrip": false,
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+ "single_word": false,
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+ "special": true
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+ },
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+ "128226": {
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+ "single_word": false,
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+ "special": true
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+ },
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+ "128227": {
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+ "special": true
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+ },
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+ "128228": {
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+ "content": "<|reserved_special_token_220|>",
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+ "single_word": false,
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+ "special": true
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+ },
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+ "128229": {
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+ "content": "<|reserved_special_token_221|>",
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+ "special": true
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+ },
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+ "128230": {
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+ "content": "<|reserved_special_token_222|>",
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+ "lstrip": false,
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+ "single_word": false,
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+ "special": true
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+ },
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+ "128231": {
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+ "content": "<|reserved_special_token_223|>",
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+ "normalized": false,
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+ "rstrip": false,
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+ "single_word": false,
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+ "special": true
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+ },
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+ "128232": {
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+ "content": "<|reserved_special_token_224|>",
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+ "lstrip": false,
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+ "normalized": false,
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+ "rstrip": false,
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+ "single_word": false,
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+ "special": true
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+ },
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+ "128233": {
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+ "content": "<|reserved_special_token_225|>",
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+ "normalized": false,
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+ "single_word": false,
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+ "special": true
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+ },
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+ "128234": {
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+ "content": "<|reserved_special_token_226|>",
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+ "single_word": false,
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+ "special": true
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+ },
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+ "128235": {
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+ "content": "<|reserved_special_token_227|>",
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+ "lstrip": false,
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+ "normalized": false,
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+ "single_word": false,
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+ "special": true
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+ },
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+ "128236": {
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+ "content": "<|reserved_special_token_228|>",
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+ "lstrip": false,
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+ "normalized": false,
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+ "rstrip": false,
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+ "single_word": false,
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+ "special": true
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+ },
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+ "128237": {
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+ "content": "<|reserved_special_token_229|>",
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+ "normalized": false,
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+ "single_word": false,
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+ "special": true
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+ },
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+ "128238": {
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+ "content": "<|reserved_special_token_230|>",
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+ "lstrip": false,
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+ "normalized": false,
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+ "rstrip": false,
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+ "single_word": false,
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+ "special": true
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+ },
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+ "128239": {
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+ "content": "<|reserved_special_token_231|>",
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+ "lstrip": false,
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+ "normalized": false,
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+ "rstrip": false,
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+ "single_word": false,
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+ "special": true
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+ },
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+ "128240": {
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+ "content": "<|reserved_special_token_232|>",
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+ "lstrip": false,
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+ "normalized": false,
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+ "rstrip": false,
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+ "single_word": false,
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+ "special": true
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+ },
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+ "128241": {
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+ "content": "<|reserved_special_token_233|>",
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+ "lstrip": false,
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+ "normalized": false,
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+ "single_word": false,
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+ "special": true
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+ },
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+ "128242": {
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+ "content": "<|reserved_special_token_234|>",
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+ "lstrip": false,
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+ "normalized": false,
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+ "rstrip": false,
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+ "single_word": false,
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+ "special": true
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+ },
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+ "128243": {
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+ "content": "<|reserved_special_token_235|>",
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+ "lstrip": false,
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+ "normalized": false,
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+ "rstrip": false,
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+ "single_word": false,
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+ "special": true
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+ },
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+ "128244": {
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+ "content": "<|reserved_special_token_236|>",
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+ "lstrip": false,
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+ "normalized": false,
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+ "rstrip": false,
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+ "single_word": false,
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+ "special": true
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+ },
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+ "128245": {
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+ "content": "<|reserved_special_token_237|>",
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+ "lstrip": false,
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+ "normalized": false,
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+ "single_word": false,
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+ "special": true
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+ },
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+ "128246": {
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+ "content": "<|reserved_special_token_238|>",
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+ "lstrip": false,
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+ "normalized": false,
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+ "rstrip": false,
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+ "single_word": false,
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+ "special": true
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+ },
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+ "128247": {
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+ "content": "<|reserved_special_token_239|>",
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+ "lstrip": false,
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+ "normalized": false,
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+ "rstrip": false,
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+ "single_word": false,
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+ "special": true
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+ },
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+ "128248": {
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+ "content": "<|reserved_special_token_240|>",
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+ "lstrip": false,
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+ "normalized": false,
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+ "rstrip": false,
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+ "single_word": false,
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+ "special": true
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+ },
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+ "128249": {
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+ "content": "<|reserved_special_token_241|>",
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+ "lstrip": false,
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+ "normalized": false,
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+ "rstrip": false,
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+ "single_word": false,
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+ "special": true
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+ },
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+ "128250": {
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+ "content": "<|reserved_special_token_242|>",
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+ "lstrip": false,
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+ "normalized": false,
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+ "rstrip": false,
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+ "single_word": false,
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+ "special": true
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+ },
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+ "128251": {
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+ "content": "<|reserved_special_token_243|>",
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+ "lstrip": false,
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+ "normalized": false,
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+ "rstrip": false,
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+ "single_word": false,
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+ "special": true
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+ },
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+ "128252": {
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+ "content": "<|reserved_special_token_244|>",
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+ "lstrip": false,
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+ "normalized": false,
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+ "rstrip": false,
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+ "single_word": false,
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+ "special": true
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+ },
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+ "128253": {
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+ "content": "<|reserved_special_token_245|>",
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+ "lstrip": false,
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+ "normalized": false,
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+ "rstrip": false,
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+ "single_word": false,
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+ "special": true
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+ },
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+ "128254": {
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+ "content": "<|reserved_special_token_246|>",
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+ "lstrip": false,
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+ "normalized": false,
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+ "rstrip": false,
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+ "single_word": false,
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+ "special": true
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+ },
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+ "128255": {
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+ "content": "<|reserved_special_token_247|>",
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+ "lstrip": false,
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+ "normalized": false,
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+ "rstrip": false,
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+ "single_word": false,
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+ "special": true
2050
+ }
2051
+ },
2052
+ "bos_token": "<|begin_of_text|>",
2053
+ "chat_template": "{{- bos_token }}\n{%- if custom_tools is defined %}\n {%- set tools = custom_tools %}\n{%- endif %}\n{%- if not tools_in_user_message is defined %}\n {%- set tools_in_user_message = true %}\n{%- endif %}\n{%- if not date_string is defined %}\n {%- if strftime_now is defined %}\n {%- set date_string = strftime_now(\"%d %b %Y\") %}\n {%- else %}\n {%- set date_string = \"26 Jul 2024\" %}\n {%- endif %}\n{%- endif %}\n{%- if not tools is defined %}\n {%- set tools = none %}\n{%- endif %}\n\n{#- This block extracts the system message, so we can slot it into the right place. #}\n{%- if messages[0]['role'] == 'system' %}\n {%- set system_message = messages[0]['content']|trim %}\n {%- set messages = messages[1:] %}\n{%- else %}\n {%- set system_message = \"\" %}\n{%- endif %}\n\n{#- System message #}\n{{- \"<|start_header_id|>system<|end_header_id|>\\n\\n\" }}\n{%- if tools is not none %}\n {{- \"Environment: ipython\\n\" }}\n{%- endif %}\n{{- \"Cutting Knowledge Date: December 2023\\n\" }}\n{{- \"Today Date: \" + date_string + \"\\n\\n\" }}\n{%- if tools is not none and not tools_in_user_message %}\n {{- \"You have access to the following functions. To call a function, please respond with JSON for a function call.\" }}\n {{- 'Respond in the format {\"name\": function name, \"parameters\": dictionary of argument name and its value}.' }}\n {{- \"Do not use variables.\\n\\n\" }}\n {%- for t in tools %}\n {{- t | tojson(indent=4) }}\n {{- \"\\n\\n\" }}\n {%- endfor %}\n{%- endif %}\n{{- system_message }}\n{{- \"<|eot_id|>\" }}\n\n{#- Custom tools are passed in a user message with some extra guidance #}\n{%- if tools_in_user_message and not tools is none %}\n {#- Extract the first user message so we can plug it in here #}\n {%- if messages | length != 0 %}\n {%- set first_user_message = messages[0]['content']|trim %}\n {%- set messages = messages[1:] %}\n {%- else %}\n {{- raise_exception(\"Cannot put tools in the first user message when there's no first user message!\") }}\n{%- endif %}\n {{- '<|start_header_id|>user<|end_header_id|>\\n\\n' -}}\n {{- \"Given the following functions, please respond with a JSON for a function call \" }}\n {{- \"with its proper arguments that best answers the given prompt.\\n\\n\" }}\n {{- 'Respond in the format {\"name\": function name, \"parameters\": dictionary of argument name and its value}.' }}\n {{- \"Do not use variables.\\n\\n\" }}\n {%- for t in tools %}\n {{- t | tojson(indent=4) }}\n {{- \"\\n\\n\" }}\n {%- endfor %}\n {{- first_user_message + \"<|eot_id|>\"}}\n{%- endif %}\n\n{%- for message in messages %}\n {%- if not (message.role == 'ipython' or message.role == 'tool' or 'tool_calls' in message) %}\n {{- '<|start_header_id|>' + message['role'] + '<|end_header_id|>\\n\\n'+ message['content'] | trim + '<|eot_id|>' }}\n {%- elif 'tool_calls' in message %}\n {%- if not message.tool_calls|length == 1 %}\n {{- raise_exception(\"This model only supports single tool-calls at once!\") }}\n {%- endif %}\n {%- set tool_call = message.tool_calls[0].function %}\n {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' -}}\n {{- '{\"name\": \"' + tool_call.name + '\", ' }}\n {{- '\"parameters\": ' }}\n {{- tool_call.arguments | tojson }}\n {{- \"}\" }}\n {{- \"<|eot_id|>\" }}\n {%- elif message.role == \"tool\" or message.role == \"ipython\" %}\n {{- \"<|start_header_id|>ipython<|end_header_id|>\\n\\n\" }}\n {%- if message.content is mapping or message.content is iterable %}\n {{- message.content | tojson }}\n {%- else %}\n {{- message.content }}\n {%- endif %}\n {{- \"<|eot_id|>\" }}\n {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' }}\n{%- endif %}\n",
2054
+ "clean_up_tokenization_spaces": true,
2055
+ "eos_token": "<|eot_id|>",
2056
+ "model_input_names": [
2057
+ "input_ids",
2058
+ "attention_mask"
2059
+ ],
2060
+ "model_max_length": 131072,
2061
+ "pad_token": "<|eot_id|>",
2062
+ "padding_side": "right",
2063
+ "split_special_tokens": false,
2064
+ "tokenizer_class": "PreTrainedTokenizerFast"
2065
+ }
checkpoint-400/trainer_state.json ADDED
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+ version https://git-lfs.github.com/spec/v1
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+ size 17209920
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+ "bos_token": "<|begin_of_text|>",
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+ "chat_template": "{{- bos_token }}\n{%- if custom_tools is defined %}\n {%- set tools = custom_tools %}\n{%- endif %}\n{%- if not tools_in_user_message is defined %}\n {%- set tools_in_user_message = true %}\n{%- endif %}\n{%- if not date_string is defined %}\n {%- if strftime_now is defined %}\n {%- set date_string = strftime_now(\"%d %b %Y\") %}\n {%- else %}\n {%- set date_string = \"26 Jul 2024\" %}\n {%- endif %}\n{%- endif %}\n{%- if not tools is defined %}\n {%- set tools = none %}\n{%- endif %}\n\n{#- This block extracts the system message, so we can slot it into the right place. #}\n{%- if messages[0]['role'] == 'system' %}\n {%- set system_message = messages[0]['content']|trim %}\n {%- set messages = messages[1:] %}\n{%- else %}\n {%- set system_message = \"\" %}\n{%- endif %}\n\n{#- System message #}\n{{- \"<|start_header_id|>system<|end_header_id|>\\n\\n\" }}\n{%- if tools is not none %}\n {{- \"Environment: ipython\\n\" }}\n{%- endif %}\n{{- \"Cutting Knowledge Date: December 2023\\n\" }}\n{{- \"Today Date: \" + date_string + \"\\n\\n\" }}\n{%- if tools is not none and not tools_in_user_message %}\n {{- \"You have access to the following functions. To call a function, please respond with JSON for a function call.\" }}\n {{- 'Respond in the format {\"name\": function name, \"parameters\": dictionary of argument name and its value}.' }}\n {{- \"Do not use variables.\\n\\n\" }}\n {%- for t in tools %}\n {{- t | tojson(indent=4) }}\n {{- \"\\n\\n\" }}\n {%- endfor %}\n{%- endif %}\n{{- system_message }}\n{{- \"<|eot_id|>\" }}\n\n{#- Custom tools are passed in a user message with some extra guidance #}\n{%- if tools_in_user_message and not tools is none %}\n {#- Extract the first user message so we can plug it in here #}\n {%- if messages | length != 0 %}\n {%- set first_user_message = messages[0]['content']|trim %}\n {%- set messages = messages[1:] %}\n {%- else %}\n {{- raise_exception(\"Cannot put tools in the first user message when there's no first user message!\") }}\n{%- endif %}\n {{- '<|start_header_id|>user<|end_header_id|>\\n\\n' -}}\n {{- \"Given the following functions, please respond with a JSON for a function call \" }}\n {{- \"with its proper arguments that best answers the given prompt.\\n\\n\" }}\n {{- 'Respond in the format {\"name\": function name, \"parameters\": dictionary of argument name and its value}.' }}\n {{- \"Do not use variables.\\n\\n\" }}\n {%- for t in tools %}\n {{- t | tojson(indent=4) }}\n {{- \"\\n\\n\" }}\n {%- endfor %}\n {{- first_user_message + \"<|eot_id|>\"}}\n{%- endif %}\n\n{%- for message in messages %}\n {%- if not (message.role == 'ipython' or message.role == 'tool' or 'tool_calls' in message) %}\n {{- '<|start_header_id|>' + message['role'] + '<|end_header_id|>\\n\\n'+ message['content'] | trim + '<|eot_id|>' }}\n {%- elif 'tool_calls' in message %}\n {%- if not message.tool_calls|length == 1 %}\n {{- raise_exception(\"This model only supports single tool-calls at once!\") }}\n {%- endif %}\n {%- set tool_call = message.tool_calls[0].function %}\n {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' -}}\n {{- '{\"name\": \"' + tool_call.name + '\", ' }}\n {{- '\"parameters\": ' }}\n {{- tool_call.arguments | tojson }}\n {{- \"}\" }}\n {{- \"<|eot_id|>\" }}\n {%- elif message.role == \"tool\" or message.role == \"ipython\" %}\n {{- \"<|start_header_id|>ipython<|end_header_id|>\\n\\n\" }}\n {%- if message.content is mapping or message.content is iterable %}\n {{- message.content | tojson }}\n {%- else %}\n {{- message.content }}\n {%- endif %}\n {{- \"<|eot_id|>\" }}\n {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' }}\n{%- endif %}\n",
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+ "clean_up_tokenization_spaces": true,
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+ "eos_token": "<|eot_id|>",
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+ "model_input_names": [
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+ "input_ids",
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+ "attention_mask"
2059
+ ],
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+ "model_max_length": 131072,
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+ "pad_token": "<|eot_id|>",
2062
+ "padding_side": "right",
2063
+ "split_special_tokens": false,
2064
+ "tokenizer_class": "PreTrainedTokenizerFast"
2065
+ }
train_results.json ADDED
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+ }
trainer_log.jsonl ADDED
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trainer_state.json ADDED
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