Instructions to use ipetrukha/CodeQwen1.5-7B-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use ipetrukha/CodeQwen1.5-7B-4bit 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("ipetrukha/CodeQwen1.5-7B-4bit") prompt = "Once upon a time in" text = generate(model, tokenizer, prompt=prompt, verbose=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- MLX LM
How to use ipetrukha/CodeQwen1.5-7B-4bit with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Generate some text mlx_lm.generate --model "ipetrukha/CodeQwen1.5-7B-4bit" --prompt "Once upon a time"
b55f1af7122a1de8472938fcd56559cfc3e03d838239fec955b19406879cc472
Browse files- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:a54ed5d61f3d352c8353fc075ee8a71fd68221e90faec56cca68192bc13f8b39
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size 4078997845
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