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Llama-2-13b-guanaco

πŸ“ Article | πŸ’» Colab | πŸ“„ Script

This is a llama-2-13b-chat-hf model fine-tuned using QLoRA (4-bit precision) on the mlabonne/guanaco-llama2 dataset.

πŸ”§ Training

It was trained on a Google Colab notebook with a T4 GPU and high RAM.

πŸ’» Usage

# pip install transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "mlabonne/llama-2-13b-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']}")
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Dataset used to train mlabonne/llama-2-13b-guanaco

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