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  license: cc-by-sa-4.0
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  license: cc-by-sa-4.0
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+
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+ # **Synatra-10.7B-v0.4🐧**
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+ ![Synatra-10.7B-v0.4](./Synatra.png)
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+
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+ # **License**
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+
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+ This model is strictly [*non-commercial*](https://creativecommons.org/licenses/by-sa/4.0/) (**cc-by-sa-4.0**) use.
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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-sa-4.0** license in any parent repository, and the non-commercial use statute remains, regardless of other models' licences.
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+ # **Model Details**
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+
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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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+
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+ **Trained On**
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+ A100 80GB * 1
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+
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+ **Instruction format**
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+
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+ It follows **Alpaca** format.
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+
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+ # **Model Benchmark**
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+
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+
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+ ## Ko-LLM-Leaderboard
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+
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+ On Benchmarking...
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+
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+ # **Implementation Code**
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+
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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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+
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+ ```python
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+ from transformers import AutoModelForCausalLM, AutoTokenizer
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+
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+ device = "cuda" # the device to load the model onto
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+
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+ model = AutoModelForCausalLM.from_pretrained("maywell/Synatra-10.7B-v0.4")
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+ tokenizer = AutoTokenizer.from_pretrained("maywell/Synatra-10.7B-v0.4")
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+
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+ messages = [
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+ {"role": "user", "content": "λ°”λ‚˜λ‚˜λŠ” μ›λž˜ ν•˜μ–€μƒ‰μ΄μ•Ό?"},
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+ ]
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+
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+ encodeds = tokenizer.apply_chat_template(messages, return_tensors="pt")
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+
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+ model_inputs = encodeds.to(device)
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+ model.to(device)
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+
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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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+ ```