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---
library_name: transformers
tags:
- code
datasets:
- Replete-AI/code_bagel
language:
- en
license: llama3
---
# Model Card for Llama 3 8B SFT Code Bagel
<!-- Provide a quick summary of what the model is/does. -->
## 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]
```python
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) :])
``` |