DeepMount00
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Update README.md
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README.md
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@@ -33,6 +33,37 @@ The performance of Qwen2 1.5B was evaluated on several benchmarks and compared a
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| Qwen2-1.5B-Ita | 1.5B | **43.98** | **51.45** | 32.34 | 48.15 |
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### Conclusion
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| Qwen2-1.5B-Ita | 1.5B | **43.98** | **51.45** | 32.34 | 48.15 |
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## How to Use
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```python
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import torch
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from transformers import AutoTokenizer, AutoModelForCausalLM
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model_name = "DeepMount00/Qwen2-1.5B-Ita"
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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model = AutoModelForCausalLM.from_pretrained(
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model_name,
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torch_dtype=torch.bfloat16,
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device_map="auto",
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)
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prompt = [{'role': 'user', 'content': """Marco ha comprato 5 scatole di cioccolatini. Ogni scatola contiene 12 cioccolatini. Ha deciso di dare 3 cioccolatini a ciascuno dei suoi 7 amici. Quanti cioccolatini gli rimarranno dopo averli distribuiti ai suoi amici?"""}]
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inputs = tokenizer.apply_chat_template(
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prompt,
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add_generation_prompt=True,
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return_tensors='pt'
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)
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tokens = model.generate(
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inputs.to(model.device),
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max_new_tokens=1024,
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temperature=0.001,
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do_sample=True
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)
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print(tokenizer.decode(tokens[0], skip_special_tokens=False))
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```
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### Conclusion
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