Feature Extraction
Transformers
Safetensors
qwen3_5
matilda
jev
fp4
quantized
maincode
8-bit precision
Instructions to use Maincode/Matilda-Jev-v1-FP4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Maincode/Matilda-Jev-v1-FP4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Maincode/Matilda-Jev-v1-FP4")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("Maincode/Matilda-Jev-v1-FP4") model = AutoModel.from_pretrained("Maincode/Matilda-Jev-v1-FP4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download kev/py.typed from Maincode/Matilda-Jev-v1-FP4: direct link, hf CLI and curl.
- Browser
- Download file 0 Bytes
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https://huggingface.co/Maincode/Matilda-Jev-v1-FP4/resolve/main/kev/py.typed
- Command line
-
hf download hf://Maincode/Matilda-Jev-v1-FP4/kev/py.typed
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curl -L -o py.typed https://huggingface.co/Maincode/Matilda-Jev-v1-FP4/resolve/main/kev/py.typed
0 Bytes