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README.md

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+
+---
+
+library_name: transformers
+license: apache-2.0
+language:
+- it
+- en
+datasets:
+- DeepMount00/Sonnet-3.5-ITA-INSTRUCTION
+- DeepMount00/Sonnet-3.5-ITA-DPO
+
+---
+
+[![QuantFactory Banner](https://lh7-rt.googleusercontent.com/docsz/AD_4nXeiuCm7c8lEwEJuRey9kiVZsRn2W-b4pWlu3-X534V3YmVuVc2ZL-NXg2RkzSOOS2JXGHutDuyyNAUtdJI65jGTo8jT9Y99tMi4H4MqL44Uc5QKG77B0d6-JfIkZHFaUA71-RtjyYZWVIhqsNZcx8-OMaA?key=xt3VSDoCbmTY7o-cwwOFwQ)](https://hf.co/QuantFactory)
+
+
+# QuantFactory/Lexora-Medium-7B-GGUF
+This is quantized version of [DeepMount00/Lexora-Medium-7B](https://huggingface.co/DeepMount00/Lexora-Medium-7B) created using llama.cpp
+
+# Original Model Card
+
+
+## How to Use
+
+```python
+import torch
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+model_name = "DeepMount00/Lexora-Medium-7B"
+
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(
+    model_name,
+    torch_dtype=torch.bfloat16,
+    device_map="auto",
+)
+
+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?"""}]
+inputs = tokenizer.apply_chat_template(
+    prompt,
+    add_generation_prompt=True,
+    return_tensors='pt'
+)
+tokens = model.generate(
+    inputs.to(model.device),
+    max_new_tokens=1024,
+    temperature=0.001,
+    do_sample=True
+)
+
+print(tokenizer.decode(tokens[0], skip_special_tokens=False))
+```