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+ ---
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+ language:
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+ - it
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+ - en
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+ license: llama3
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+ library_name: transformers
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+ base_model: DeepMount00/Llama-3-8b-Ita
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+ datasets:
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+ - DeepMount00/llm_ita_ultra
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+ ---
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+ # QuantFactory/Llama-3-8b-Ita-GGUF
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+ This is quantized version of [DeepMount00/Llama-3-8b-Ita](https://huggingface.co/DeepMount00/Llama-3-8b-Ita) created using llama.cpp
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+
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+ ## Model Description
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+ - **Base Model:** [Meta-Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B)
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+ - **Specialization:** Italian Language
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+
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+ ## Evaluation
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+
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+ For a detailed comparison of model performance, check out the [Leaderboard for Italian Language Models](https://huggingface.co/spaces/FinancialSupport/open_ita_llm_leaderboard).
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+
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+ Here's a breakdown of the performance metrics:
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+
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+ | Metric | hellaswag_it acc_norm | arc_it acc_norm | m_mmlu_it 5-shot acc | Average |
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+ |:----------------------------|:----------------------|:----------------|:---------------------|:--------|
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+ | **Accuracy Normalized** | 0.6518 | 0.5441 | 0.5729 | 0.5896 |
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+
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+ ---
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+
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+ ## How to Use
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+
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+ ```python
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+ from transformers import AutoModelForCausalLM, AutoTokenizer
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+ import torch
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+ device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
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+
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+ MODEL_NAME = "DeepMount00/Llama-3-8b-Ita"
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+
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+ model = AutoModelForCausalLM.from_pretrained(MODEL_NAME, torch_dtype=torch.bfloat16).eval()
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+ model.to(device)
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+ tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
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+
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+ def generate_answer(prompt):
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+ messages = [
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+ {"role": "user", "content": prompt},
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+ ]
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+ model_inputs = tokenizer.apply_chat_template(messages, return_tensors="pt").to(device)
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+ generated_ids = model.generate(model_inputs, max_new_tokens=200, do_sample=True,
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+ temperature=0.001)
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+ decoded = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)
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+ return decoded[0]
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+
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+ prompt = "Come si apre un file json in python?"
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+ answer = generate_answer(prompt)
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+ print(answer)
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+ ```
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+ ---
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+ ## Developer
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+ [Michele Montebovi]