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ipetrukha
/
CodeQwen1.5-7B-4bit

Text Generation
MLX
Safetensors
English
qwen2
pretrained
Model card Files Files and versions
xet
Community
1

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
  • 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"
CodeQwen1.5-7B-4bit
4.08 GB
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  • 1 contributor
History: 2 commits
ipetrukha's picture
ipetrukha
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  • .gitattributes
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  • README.md
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  • config.json
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  • model.safetensors
    4.08 GB
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  • model.safetensors.index.json
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  • special_tokens_map.json
    727 Bytes
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  • tokenizer.json
    4.46 MB
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  • tokenizer.model
    500 kB
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  • tokenizer_config.json
    237 kB
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