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---
license: apache-2.0
language:
- it
- en
library_name: transformers
tags:
- sft
- it
- mistral
- chatml
---
# Model Information
xxxx is a SFT and LoRA finetuned version of Mistral-7B-v0.2
It has been trained on a mixture of opensource datasets, like SQUAD-it (https://huggingface.co/datasets/squad_it), and some internally made datasets.
It is not just a Q&A, it is a Q&A + Context model, with the goal being it being used for RAGs and application in need of a context.
## Usage
```python
from transformers import AutoModelForCausalLM, AutoTokenizer
device = "cuda"
model = AutoModelForCausalLM.from_pretrained("MoxoffSpA/xxxx")
tokenizer = AutoTokenizer.from_pretrained("MoxoffSpA/xxxx")
question = """Quanto è alta la torre di Pisa?"""
context = """
La Torre di Pisa è un campanile del XII secolo, famoso per la sua inclinazione. Alta circa 56 metri.
"""
prompt = f"Rispondi alla seguente domanda con meno parle possibili basandoti sul contesto fornito. Domanda: {question}, contesto: {context}"
messages = [
{"role": "user", "content": prompt},
]
encodeds = tokenizer.apply_chat_template(messages, return_tensors="pt")
model_inputs = encodeds.to(device)
model.to(device)
generated_ids = model.generate(model_inputs, max_new_tokens=1000, do_sample=True)
decoded = tokenizer.batch_decode(generated_ids)
print(decoded[0])
```
## The Moxoff Team
Marco D'Ambra, Jacopo Abate, Gianpaolo Francesco Trotta |