---

library_name: transformers
license: apache-2.0
language:
- it
- en
datasets:
- DeepMount00/Sonnet-3.5-ITA-INSTRUCTION
- DeepMount00/Sonnet-3.5-ITA-DPO

---

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# 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))
```