---
license: other
language:
- en
pipeline_tag: text-generation
inference: false
tags:
- transformers
- gguf
- imatrix
- Saul-Instruct-v1
---
Quantizations of https://huggingface.co./Equall/Saul-Instruct-v1

# From original readme

## Uses

<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
You can use it for legal use cases that involves generation.

Here's how you can run the model using the pipeline() function from 🤗 Transformers:

```python

# Install transformers from source - only needed for versions <= v4.34
# pip install git+https://github.com/huggingface/transformers.git
# pip install accelerate

import torch
from transformers import pipeline

pipe = pipeline("text-generation", model="Equall/Saul-Instruct-v1", torch_dtype=torch.bfloat16, device_map="auto")
# We use the tokenizer’s chat template to format each message - see https://huggingface.co./docs/transformers/main/en/chat_templating
messages = [
    {"role": "user", "content": "[YOUR QUERY GOES HERE]"},
]
prompt = pipe.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
outputs = pipe(prompt, max_new_tokens=256, do_sample=False)
print(outputs[0]["generated_text"])
```