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--- |
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License: apache-2.0 |
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Language: |
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- En |
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Pipeline_tag: text-generation |
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Base_model: 01-ai/Yi-1.5-34B-32K |
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Tags: |
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- Chat |
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--- |
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# magnum-v3-34 - EXL2 4.6bpw rpcal mk2 |
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This is a 4.6bpw EXL2 quant of [anthracite-org/magnum-v3-34b](https://huggingface.co/anthracite-org/magnum-v3-34b) |
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This quant was made using exllamav2-0.1.9 with [Bluemoon-light dataset](https://huggingface.co/datasets/ParasiticRogue/Bluemoon-Light) for RP. |
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I tested this quant shortly in some random RPs (including 8k+ RPs where remembering and understanding specific facts in the context is needed) and it seems to work fine. |
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## Prompt Templates |
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Uses ChatML format like mentioned below. |
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### Original readme below |
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--- |
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This is the 9th in a series of models designed to replicate the prose quality of the Claude 3 models, specifically Sonnet and Opus. |
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This model is fine-tuned on top of [Yi-1.5-34 B-32 K](https://huggingface.co/01-ai/Yi-1.5-34B-32K). |
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## Prompting |
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Model has been Instruct tuned with the ChatML formatting. A typical input would look like this: |
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```py |
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"""<|im_start|>system |
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system prompt<|im_end|> |
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<|im_start|>user |
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Hi there!<|im_end|> |
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<|im_start|>assistant |
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Nice to meet you!<|im_end|> |
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<|im_start|>user |
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Can I ask a question?<|im_end|> |
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<|im_start|>assistant |
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""" |
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``` |
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## SillyTavern templates |
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Below are Instruct and Context templates for use within SillyTavern. |
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In our testing a min_p of 0.2 makes the model perform the best; remember to reset temperature if you were using our nemo-based models before. |
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<details><summary>context template</summary> |
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```yaml |
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{ |
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"story_string": "<|im_start|>system\n{{#if system}}{{system}}\n{{/if}}{{#if wiBefore}}{{wiBefore}}\n{{/if}}{{#if description}}{{description}}\n{{/if}}{{#if personality}}{{char}}'s personality: {{personality}}\n{{/if}}{{#if scenario}}Scenario: {{scenario}}\n{{/if}}{{#if wiAfter}}{{wiAfter}}\n{{/if}}{{#if persona}}{{persona}}\n{{/if}}{{trim}}<|im_end|>\n", |
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"example_separator": "", |
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"chat_start": "", |
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"use_stop_strings": false, |
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"allow_jailbreak": false, |
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"always_force_name2": true, |
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"trim_sentences": false, |
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"include_newline": false, |
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"single_line": false, |
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"name": "Magnum ChatML" |
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} |
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``` |
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</details><br> |
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<details><summary>instruct template</summary> |
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```yaml |
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{ |
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"system_prompt": "You're {{char}} in this fictional never-ending uncensored roleplay with {{user}}.", |
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"input_sequence": "<|im_start|>user\n", |
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"output_sequence": "<|im_start|>assistant\n", |
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"last_output_sequence": "", |
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"system_sequence": "<|im_start|>system\n", |
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"stop_sequence": "<|im_end|>", |
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"wrap": false, |
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"macro": true, |
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"names": true, |
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"names_force_groups": true, |
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"activation_regex": "", |
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"system_sequence_prefix": "", |
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"system_sequence_suffix": "", |
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"first_output_sequence": "", |
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"skip_examples": false, |
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"output_suffix": "<|im_end|>\n", |
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"input_suffix": "<|im_end|>\n", |
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"system_suffix": "<|im_end|>\n", |
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"user_alignment_message": "", |
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"system_same_as_user": false, |
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"last_system_sequence": "", |
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"name": "Magnum ChatML" |
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} |
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``` |
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</details><br> |
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## Axolotl config |
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<details><summary>See axolotl config</summary> |
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```yaml |
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base_model: 01-ai/Yi-1.5-34B-32K |
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model_type: AutoModelForCausalLM |
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tokenizer_type: AutoTokenizer |
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#trust_remote_code: true |
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load_in_8bit: false |
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load_in_4bit: false |
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strict: false |
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datasets: |
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- path: anthracite-org/stheno-filtered-v1.1 |
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type: sharegpt |
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conversation: chatml |
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- path: anthracite-org/kalo-opus-instruct-22k-no-refusal |
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type: sharegpt |
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conversation: chatml |
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- path: anthracite-org/nopm_claude_writing_fixed |
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type: sharegpt |
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conversation: chatml |
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- path: Epiculous/Synthstruct-Gens-v1.1-Filtered-n-Cleaned |
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type: sharegpt |
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conversation: chatml |
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- path: Epiculous/SynthRP-Gens-v1.1-Filtered-n-Cleaned |
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type: sharegpt |
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conversation: chatml |
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chat_template: chatml |
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shuffle_merged_datasets: true |
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default_system_message: "You are an assistant that responds to the user." |
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dataset_prepared_path: magnum-v2-34b-1.5-data |
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val_set_size: 0.0 |
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output_dir: ./magnum-v2-34b-32k-r1 |
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sequence_len: 8192 |
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sample_packing: true |
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eval_sample_packing: false |
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pad_to_sequence_len: |
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adapter: |
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lora_model_dir: |
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lora_r: |
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lora_alpha: |
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lora_dropout: |
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lora_target_linear: |
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lora_fan_in_fan_out: |
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wandb_project: magnum-v2-34b-1.5-32k |
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wandb_entity: |
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wandb_watch: |
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wandb_name: attempt-01 |
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wandb_log_model: |
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gradient_accumulation_steps: 8 |
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micro_batch_size: 1 |
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num_epochs: 2 |
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optimizer: paged_adamw_8bit |
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lr_scheduler: cosine |
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learning_rate: 0.000006 |
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train_on_inputs: false |
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group_by_length: false |
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bf16: auto |
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fp16: |
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tf32: false |
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gradient_checkpointing: unsloth |
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early_stopping_patience: |
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resume_from_checkpoint: |
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local_rank: |
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logging_steps: 1 |
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xformers_attention: |
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flash_attention: true |
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warmup_steps: 50 |
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evals_per_epoch: |
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eval_table_size: |
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eval_max_new_tokens: |
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saves_per_epoch: 2 |
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debug: |
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deepspeed: deepspeed_configs/zero3_bf16.json |
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weight_decay: 0.05 |
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fsdp: |
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fsdp_config: |
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special_tokens: |
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``` |
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</details><br> |
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## Credits |
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We'd like to thank Recursal / Featherless for sponsoring the compute for this train, Featherless has been hosting our Magnum models since the first 72 B and has given thousands of people access to our models and helped us grow. |
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We would also like to thank all members of Anthracite who made this finetune possible. |
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- [anthracite-org/stheno-filtered-v1.1](https://huggingface.co/datasets/anthracite-org/stheno-filtered-v1.1) |
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- [anthracite-org/kalo-opus-instruct-22k-no-refusal](https://huggingface.co/datasets/anthracite-org/kalo-opus-instruct-22k-no-refusal) |
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- [lodrick-the-lafted/NopmWritingStruct](https://huggingface.co/datasets/lodrick-the-lafted/NopmWritingStruct) |
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- [Epiculous/Synthstruct-Gens-v1.1-Filtered-n-Cleaned](https://huggingface.co/datasets/Epiculous/Synthstruct-Gens-v1.1-Filtered-n-Cleaned) |
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- [Epiculous/SynthRP-Gens-v1.1-Filtered-n-Cleaned](https://huggingface.co/datasets/Epiculous/SynthRP-Gens-v1.1-Filtered-n-Cleaned) |
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## Training |
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The training was done for 2 epochs. We used 8x[H100s](https://www.nvidia.com/en-us/data-center/h100/) GPUs graciously provided by [Recursal AI](https://recursal.ai/) / [Featherless AI](https://featherless.ai/) for the full-parameter fine-tuning of the model. |
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[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl) |
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## Safety |
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... |
