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--- |
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tags: |
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- text-generation |
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license: cc-by-nc-sa-4.0 |
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language: |
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- ko |
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base_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0 |
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pipeline_tag: text-generation |
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--- |
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# **DataVortexTL-1.1B-v0.1** |
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<img src="./DataVortex.png" alt="DataVortex" style="height: 8em;"> |
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## **License** |
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[cc-by-nc-sa-4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/) |
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## **Model Details** |
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### **Base Model** |
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[TinyLlama/TinyLlama-1.1B-Chat-v1.0](https://huggingface.co./TinyLlama/TinyLlama-1.1B-Chat-v1.0) |
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### **Trained On** |
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H100 80GB 1ea |
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### **Instruction format** |
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<!-- It follows **(No Input) Alpaca** format. --> |
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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" |
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model = AutoModelForCausalLM.from_pretrained("Edentns/DataVortexTL-1.1B-v0.1", device_map=device) |
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tokenizer = AutoTokenizer.from_pretrained("Edentns/DataVortexTL-1.1B-v0.1") |
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messages = [ |
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{ "role": "user", "content": "대한민국의 수도는 어디야?" } |
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] |
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encoded = tokenizer.apply_chat_template( |
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messages, |
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add_generation_prompt=True, |
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return_tensors="pt", |
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return_token_type_ids=False |
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).to(device) |
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decoded = model.generate( |
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input_ids=encoded, |
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temperature=0.2, |
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top_p=0.9, |
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repetition_penalty=1.2, |
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do_sample=True, |
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max_length=4096, |
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eos_token_id=tokenizer.eos_token_id, |
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pad_token_id=tokenizer.eos_token_id |
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) |
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decoded = decoded[0][encoded.shape[1]:decoded[0].shape[-1]] |
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decoded_text = tokenizer.decode(decoded, skip_special_tokens=True) |
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print(decoded_text) |
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``` |
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<div align="center"> |
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<a href="https://edentns.com/"> |
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<img src="./Logo.png" alt="Logo" style="height: 3em;"> |
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</a> |
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</div> |
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