Edit model card

You need to agree to share your contact information to access this model

This repository is publicly accessible, but you have to accept the conditions to access its files and content.

Log in or Sign Up to review the conditions and access this model content.

YAML Metadata Warning: empty or missing yaml metadata in repo card (https://huggingface.co/docs/hub/model-cards#model-card-metadata)

Miniguanaco-7b Assistant Bot

Assistant Bot

This is a Miniguanaco-7b assistant bot, fine-tuned using QLoRA (4-bit precision) on the mlabonne/guanaco-llama2-1k dataset, a subset of timdettmers/openassistant-guanaco.

Training

The model was trained on a Google Colab notebook with a T4 GPU and high RAM. Please note that it is primarily designed for educational purposes and may not be optimized for production-level inference.

Usage

To use the Miniguanaco-7b assistant bot, you can follow the code example below:

# pip install transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "mlabonne/llama-2-7b-miniguanaco"
prompt = "What is a large language model?"

tokenizer = AutoTokenizer.from_pretrained(model)

pipeline = transformers.pipeline(
    "text-generation",
    model=model,
    torch_dtype=torch.float16,
    device_map="auto",
)

sequences = pipeline(
    f'<s>[INST] {prompt} [/INST]',
    do_sample=True,
    top_k=10,
    num_return_sequences=1,
    eos_token_id=tokenizer.eos_token_id,
    max_length=200,
)

for seq in sequences:
    print(f"Result: {seq['generated_text']}")
Downloads last month
0