Instructions to use xunker/CodeLens-7B-MLX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use xunker/CodeLens-7B-MLX with Transformers:

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

pipe = pipeline("text-generation", model="xunker/CodeLens-7B-MLX")

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("xunker/CodeLens-7B-MLX", dtype="auto")

MLX

How to use xunker/CodeLens-7B-MLX with MLX:

# Make sure mlx-lm is installed
# pip install --upgrade mlx-lm
# if on a CUDA device, also pip install mlx[cuda]

# Generate text with mlx-lm
from mlx_lm import load, generate

model, tokenizer = load("xunker/CodeLens-7B-MLX")

prompt = "Once upon a time in"
text = generate(model, tokenizer, prompt=prompt, verbose=True)

Notebooks
Google Colab
Kaggle
Local Apps Settings
LM Studio

vLLM

How to use xunker/CodeLens-7B-MLX with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "xunker/CodeLens-7B-MLX"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "xunker/CodeLens-7B-MLX",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/xunker/CodeLens-7B-MLX

SGLang

How to use xunker/CodeLens-7B-MLX 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 "xunker/CodeLens-7B-MLX" \
    --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": "xunker/CodeLens-7B-MLX",
		"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 "xunker/CodeLens-7B-MLX" \
        --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": "xunker/CodeLens-7B-MLX",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

MLX LM

How to use xunker/CodeLens-7B-MLX with MLX LM:

Generate or start a chat session

# Install MLX LM
uv tool install mlx-lm
# Generate some text
mlx_lm.generate --model "xunker/CodeLens-7B-MLX" --prompt "Once upon a time"

Docker Model Runner
How to use xunker/CodeLens-7B-MLX with Docker Model Runner:
```
docker model run hf.co/xunker/CodeLens-7B-MLX
```

CodeLens-7B-MLX / .gitattributes

xunker

Upload 35 files

1e57276 verified 8 days ago

Raw

History Blame Contribute Delete

2.1 kB

	*.7z filter=lfs diff=lfs merge=lfs -text
	*.arrow filter=lfs diff=lfs merge=lfs -text
	*.bin filter=lfs diff=lfs merge=lfs -text
	*.bz2 filter=lfs diff=lfs merge=lfs -text
	*.ckpt filter=lfs diff=lfs merge=lfs -text
	*.ftz filter=lfs diff=lfs merge=lfs -text
	*.gz filter=lfs diff=lfs merge=lfs -text
	*.h5 filter=lfs diff=lfs merge=lfs -text
	*.joblib filter=lfs diff=lfs merge=lfs -text
	.lfs. filter=lfs diff=lfs merge=lfs -text
	*.mlmodel filter=lfs diff=lfs merge=lfs -text
	*.model filter=lfs diff=lfs merge=lfs -text
	*.msgpack filter=lfs diff=lfs merge=lfs -text
	*.npy filter=lfs diff=lfs merge=lfs -text
	*.npz filter=lfs diff=lfs merge=lfs -text
	*.onnx filter=lfs diff=lfs merge=lfs -text
	*.ot filter=lfs diff=lfs merge=lfs -text
	*.parquet filter=lfs diff=lfs merge=lfs -text
	*.pb filter=lfs diff=lfs merge=lfs -text
	*.pickle filter=lfs diff=lfs merge=lfs -text
	*.pkl filter=lfs diff=lfs merge=lfs -text
	*.pt filter=lfs diff=lfs merge=lfs -text
	*.pth filter=lfs diff=lfs merge=lfs -text
	*.rar filter=lfs diff=lfs merge=lfs -text
	*.safetensors filter=lfs diff=lfs merge=lfs -text
	saved_model/*/ filter=lfs diff=lfs merge=lfs -text
	.tar. filter=lfs diff=lfs merge=lfs -text
	*.tar filter=lfs diff=lfs merge=lfs -text
	*.tflite filter=lfs diff=lfs merge=lfs -text
	*.tgz filter=lfs diff=lfs merge=lfs -text
	*.wasm filter=lfs diff=lfs merge=lfs -text
	*.xz filter=lfs diff=lfs merge=lfs -text
	*.zip filter=lfs diff=lfs merge=lfs -text
	*.zst filter=lfs diff=lfs merge=lfs -text
	tfevents filter=lfs diff=lfs merge=lfs -text
	CodeLens-7B-oQ8-bf16/tokenizer.json filter=lfs diff=lfs merge=lfs -text
	CodeLens-7B-oQ8-fp16/tokenizer.json filter=lfs diff=lfs merge=lfs -text
	CodeLens-7B-oQ4-bf16/tokenizer.json filter=lfs diff=lfs merge=lfs -text
	CodeLens-7B-oQ4-fp16/tokenizer.json filter=lfs diff=lfs merge=lfs -text
	CodeLens-7B-oQ5-bf16/tokenizer.json filter=lfs diff=lfs merge=lfs -text
	CodeLens-7B-oQ5-fp16/tokenizer.json filter=lfs diff=lfs merge=lfs -text
	CodeLens-7B-oQ6-bf16/tokenizer.json filter=lfs diff=lfs merge=lfs -text
	CodeLens-7B-oQ6-fp16/tokenizer.json filter=lfs diff=lfs merge=lfs -text