Instructions to use skar01/llama2-coder-full with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use skar01/llama2-coder-full with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="skar01/llama2-coder-full")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("skar01/llama2-coder-full")
model = AutoModelForCausalLM.from_pretrained("skar01/llama2-coder-full", device_map="auto")

Inference
Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use skar01/llama2-coder-full with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "skar01/llama2-coder-full"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "skar01/llama2-coder-full",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/skar01/llama2-coder-full

SGLang

How to use skar01/llama2-coder-full with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "skar01/llama2-coder-full" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "skar01/llama2-coder-full",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "skar01/llama2-coder-full" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "skar01/llama2-coder-full",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use skar01/llama2-coder-full with Docker Model Runner:
```
docker model run hf.co/skar01/llama2-coder-full
```

Llama2 (7B) model fine-tuned on the CodeAlpaca 20k instructions dataset by using the method QLoRA with PEFT library.

Training and evaluation data 📚

CodeAlpaca_20K: contains 20K instruction-following data used for fine-tuning the Code Alpaca model. Data is here: https://huggingface.co/mrm8488/falcon-7b-ft-codeAlpaca_20k The adapter is here: https://huggingface.co/skar01/llama2-coder The base model is: TinyPixel/Llama-2-7B-bf16-sharded

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