---
language: vi
tags:
- chatbot
- vietnamese
- conversational
license: mit
datasets:
- your_dataset_name
metrics:
- perplexity
- bleu
---

# Model Card for Vistral-7B-Chat

## Model Details

- **Model Name:** Vistral-7B-LegalBizAI
- **Version:** 1.0
- **Model Type:** Causal Language Model
- **Architecture:** Transformer-based model with 7 billion parameters
- **Quantization:** 8-bit quantized for efficiency

## Usage

### How to use

```python
from transformers import AutoModelForCausalLM, AutoTokenizer

model_name = "nhotin/vistral7B-legalbizai-q8-gguf"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)

input_text = "Your text here"
inputs = tokenizer(input_text, return_tensors="pt")
outputs = model.generate(**inputs)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))