Feature Extraction
Transformers
Safetensors
qwen3_5
matilda
jev
fp4
quantized
maincode
8-bit precision
Instructions to use Maincode/matilda-jev-fp4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Maincode/matilda-jev-fp4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Maincode/matilda-jev-fp4")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("Maincode/matilda-jev-fp4") model = AutoModel.from_pretrained("Maincode/matilda-jev-fp4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download kev/py.typed from Maincode/matilda-jev-fp4: direct link, hf CLI and curl.
- Browser
- Download file 0 Bytes
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https://huggingface.co/Maincode/matilda-jev-fp4/resolve/main/kev/py.typed
- Command line
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hf download hf://Maincode/matilda-jev-fp4/kev/py.typed
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curl -L -o py.typed https://huggingface.co/Maincode/matilda-jev-fp4/resolve/main/kev/py.typed
0 Bytes