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--- |
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language: |
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- ko |
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library_name: transformers |
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pipeline_tag: text-generation |
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license: cc-by-nc-4.0 |
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--- |
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곡μ λͺ¨λΈ μ£Όμ |
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https://huggingface.co/maywell/Synatra-7B-v0.3-RP |
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# **Synatra-7B-v0.3-RPπ§** |
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## Support Me |
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μλνΈλΌλ κ°μΈ νλ‘μ νΈλ‘, 1μΈμ μμμΌλ‘ κ°λ°λκ³ μμ΅λλ€. λͺ¨λΈμ΄ λ§μμ λμ
¨λ€λ©΄ μ½κ°μ μ°κ΅¬λΉ μ§μμ μ΄λ¨κΉμ? |
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[<img src="https://cdn.buymeacoffee.com/buttons/default-orange.png" alt="Buy me a Coffee" width="217" height="50">](https://www.buymeacoffee.com/mwell) |
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Wanna be a sponser? Contact me on Telegram **AlzarTakkarsen** |
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# **License** |
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This model is strictly [*non-commercial*](https://creativecommons.org/licenses/by-nc/4.0/) (**cc-by-nc-4.0**) use only. |
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The "Model" is completely free (ie. base model, derivates, merges/mixes) to use for non-commercial purposes as long as the the included **cc-by-nc-4.0** license in any parent repository, and the non-commercial use statute remains, regardless of other models' licences. |
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The licence can be changed after new model released. If you are to use this model for commercial purpose, Contact me. |
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# **Model Details** |
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**Base Model** |
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[mistralai/Mistral-7B-Instruct-v0.1](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1) |
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**Trained On** |
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A6000 48GB * 8 |
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**Instruction format** |
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It follows [ChatML](https://github.com/openai/openai-python/blob/main/chatml.md) format. |
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**TODO** |
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- ~~``RP κΈ°λ° νλ λͺ¨λΈ μ μ``~~ β
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- ~~``λ°μ΄ν°μ
μ μ ``~~ β
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- μΈμ΄ μ΄ν΄λ₯λ ₯ κ°μ |
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- ~~``μμ 보μ``~~ β
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- ν ν¬λμ΄μ λ³κ²½ |
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# **Model Benchmark** |
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## Ko-LLM-Leaderboard |
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On Benchmarking... |
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# **Implementation Code** |
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Since, chat_template already contains insturction format above. |
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You can use the code below. |
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```python |
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from transformers import AutoModelForCausalLM, AutoTokenizer |
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device = "cuda" # the device to load the model onto |
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model = AutoModelForCausalLM.from_pretrained("maywell/Synatra-7B-v0.3-RP") |
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tokenizer = AutoTokenizer.from_pretrained("maywell/Synatra-7B-v0.3-RP") |
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messages = [ |
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{"role": "user", "content": "λ°λλλ μλ νμμμ΄μΌ?"}, |
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] |
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encodeds = tokenizer.apply_chat_template(messages, return_tensors="pt") |
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model_inputs = encodeds.to(device) |
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model.to(device) |
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generated_ids = model.generate(model_inputs, max_new_tokens=1000, do_sample=True) |
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decoded = tokenizer.batch_decode(generated_ids) |
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print(decoded[0]) |
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``` |
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# Why It's benchmark score is lower than preview version? |
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**Apparently**, Preview model uses Alpaca Style prompt which has no pre-fix. But ChatML do. |
