Instructions to use waltertaya/llama2-code-lora-v2-merged with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use waltertaya/llama2-code-lora-v2-merged with Transformers:

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

pipe = pipeline("text-generation", model="waltertaya/llama2-code-lora-v2-merged")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("waltertaya/llama2-code-lora-v2-merged")
model = AutoModelForCausalLM.from_pretrained("waltertaya/llama2-code-lora-v2-merged")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use waltertaya/llama2-code-lora-v2-merged with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "waltertaya/llama2-code-lora-v2-merged"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "waltertaya/llama2-code-lora-v2-merged",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/waltertaya/llama2-code-lora-v2-merged

SGLang

How to use waltertaya/llama2-code-lora-v2-merged 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 "waltertaya/llama2-code-lora-v2-merged" \
    --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": "waltertaya/llama2-code-lora-v2-merged",
		"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 "waltertaya/llama2-code-lora-v2-merged" \
        --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": "waltertaya/llama2-code-lora-v2-merged",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use waltertaya/llama2-code-lora-v2-merged with Docker Model Runner:
```
docker model run hf.co/waltertaya/llama2-code-lora-v2-merged
```

llama2-code-lora-v2-merged

Commit History

Upload tokenizer

621df40
verified

Walter Onyango commited on Dec 14, 2025

Upload LlamaForCausalLM

2df69df
verified

Walter Onyango commited on Dec 14, 2025

initial commit

461f7d4
verified

Walter Onyango commited on Dec 14, 2025

Commit History

Upload tokenizer 621df40 verified

Upload LlamaForCausalLM 2df69df verified

initial commit 461f7d4 verified

Upload tokenizer

621df40
verified

Upload LlamaForCausalLM

2df69df
verified

initial commit

461f7d4
verified