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Jackrong
/
Qwopus3.5-9B-v3-FP8

Image-Text-to-Text
Safetensors
English
Chinese
Korean
qwen3_5_text
unsloth
qwen
qwen3.5
fp8
vllm
reasoning
chain-of-thought
lora
competitive-programming
conversational
compressed-tensors
Model card Files Files and versions
xet
Community

Instructions to use Jackrong/Qwopus3.5-9B-v3-FP8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Local Apps
  • Unsloth Studio new

    How to use Jackrong/Qwopus3.5-9B-v3-FP8 with Unsloth Studio:

    Install Unsloth Studio (macOS, Linux, WSL)
    curl -fsSL https://unsloth.ai/install.sh | sh
    # Run unsloth studio
    unsloth studio -H 0.0.0.0 -p 8888
    # Then open http://localhost:8888 in your browser
    # Search for Jackrong/Qwopus3.5-9B-v3-FP8 to start chatting
    Install Unsloth Studio (Windows)
    irm https://unsloth.ai/install.ps1 | iex
    # Run unsloth studio
    unsloth studio -H 0.0.0.0 -p 8888
    # Then open http://localhost:8888 in your browser
    # Search for Jackrong/Qwopus3.5-9B-v3-FP8 to start chatting
    Using HuggingFace Spaces for Unsloth
    # No setup required
    # Open https://huggingface.co/spaces/unsloth/studio in your browser
    # Search for Jackrong/Qwopus3.5-9B-v3-FP8 to start chatting
    Load model with FastModel
    pip install unsloth
    from unsloth import FastModel
    model, tokenizer = FastModel.from_pretrained(
        model_name="Jackrong/Qwopus3.5-9B-v3-FP8",
        max_seq_length=2048,
    )
Qwopus3.5-9B-v3-FP8
11 GB
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  • 1 contributor
History: 4 commits
Jackrong's picture
Jackrong
Update README.md
b590346 verified about 2 months ago
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  • config.json
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  • generation_config.json
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  • model.safetensors
    11 GB
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  • quantization_info.json
    473 Bytes
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  • recipe.yaml
    176 Bytes
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  • tokenizer.json
    20 MB
    xet
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  • tokenizer_config.json
    1.17 kB
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