Llama3-8B-SFT-code_bagel-bnb-4bit

Model Card for Llama 3 8B SFT Code Bagel

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Model Details

Model Description

This model, Llama3-8B-SFT-code_bagel-bnb-4bit, is a fine-tuned version of the Meta-Llama-3-8B-Instruct model, finetuned via SFT on 35k randomly selected rows from the Replete-AI/code_bagel dataset using Supervised Fine-Tuning (SFT) and quantized to 4-bit precision using the Bits and Bytes (bnb) library. It is optimized for code-related tasks.

Uses

Coding and code related tasks

How to Get Started with the Model

Use the code below to get started with the model.

[More Information Needed]

import torch
import transformers

# Load the tokenizer and model
model_id = "thesven/Llama3-8B-SFT-code_bagel-bnb-4bit"

pipeline = transformers.pipeline(
    "text-generation",
    model=model_id,
    model_kwargs={"torch_dtype": torch.bfloat16},
    device_map="auto",
)

messages = [
    {
        "role": "user",
        "content": "Write me a python function to turn every other letter in a string to uppercase?",
    },
]

prompt = pipeline.tokenizer.apply_chat_template(
    messages, tokenize=False, add_generation_prompt=True
)

terminators = [
    pipeline.tokenizer.eos_token_id,
    pipeline.tokenizer.convert_tokens_to_ids("<|eot_id|>"),
]

outputs = pipeline(
    prompt,
    max_new_tokens=256,
    eos_token_id=terminators,
    do_sample=True,
    temperature=0.1,
)
print(outputs[0]["generated_text"][len(prompt) :])