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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
---
[](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))
```
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