Goekdeniz-Guelmez
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Browse files- 9707882e31d42174567264f5c86636e980198b3c21e95056bafa6d22136e94c6 (a49df69b5b760550f0a8694c361ddec6e74f95a4)
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- README.md +39 -0
- config.json +23 -0
- model.pth +3 -0
- tokenizer.json +0 -0
- tokenizer.model +3 -0
README.md
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---
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base_model: Goekdeniz-Guelmez/j.o.s.i.e.v4o-7b-orpo-stage1-v1
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language:
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- en
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license: apache-2.0
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tags:
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- text-generation-inference
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- transformers
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- unsloth
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- qwen2
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- trl
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- orpo
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- KANama
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---
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# Goekdeniz-Guelmez/KANama-fineweb-v1-test1
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The Model [Goekdeniz-Guelmez/KANama-fineweb-v1-test1](https://huggingface.co/Goekdeniz-Guelmez/KANama-fineweb-v1-test1) was created using KANama.
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## Use with KANama
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```bash
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pip install KANama, transformers
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```
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```python
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from model.handler import from_pretrained, quick_inference
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from transformers import AutoTokenizer
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tokenizer = AutoTokenizer.from_pretrained("Doctor-Shotgun/TinyLlama-1.1B-32k")
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model = from_pretrained("path/to/model/folder")
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prompt="hello"
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input_tokens = tokenizer(prompt, return_tensors="pt").input_ids.to(device)
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generated_tokens, generated_text = quick_inference(model, input_tokens, max_new_tokens=50, tokenizer=tokenizer)
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print(generated_text)
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```
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config.json
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{
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"vocab_size": 152064,
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"pad_id": 151645,
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"eos_id": -1,
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"dim": 256,
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"n_layers": 18,
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"n_heads": 12,
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"n_kv_heads": 6,
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"use_kan": true,
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"train_softmax_temp": true,
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"use_softmax_temp_proj": true,
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"softmax_bias": false,
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"multiple_of": 256,
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"ffn_dim_multiplier": null,
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"rms_norm_eps": 1e-05,
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"rope_theta": 500000,
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"use_scaled_rope": false,
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"max_batch_size": 100,
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"max_seq_len": 128,
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"num_experts": 14,
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"num_experts_per_tok": 4,
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"model_type": "KANaMoEv1"
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}
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model.pth
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version https://git-lfs.github.com/spec/v1
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oid sha256:1a0f11cc63c408e1dabc2c4cf77bb9cad2fa575b26da401a4f22c666a495c544
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size 8504870397
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tokenizer.json
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tokenizer.model
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version https://git-lfs.github.com/spec/v1
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oid sha256:a8506e7111b80c6d8635951a02eab0f4e1a8e4e5772da83846579e97b16f61bf
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size 7031673
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