Instructions to use vegaandre/FeatureExtractionV2.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vegaandre/FeatureExtractionV2.0 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("vegaandre/FeatureExtractionV2.0") model = AutoModelForSeq2SeqLM.from_pretrained("vegaandre/FeatureExtractionV2.0", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from vegaandre/FeatureExtractionV2.0: direct link, hf CLI and curl.
- Browser
- Download file 1.63 GB
-
https://huggingface.co/vegaandre/FeatureExtractionV2.0/resolve/main/model.safetensors
- Command line
-
hf download hf://vegaandre/FeatureExtractionV2.0/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/vegaandre/FeatureExtractionV2.0/resolve/main/model.safetensors
1.63 GB
- Xet hash:
- f6d2cdfced49dec4cdb362bc7ebc55bce3c54b2cc7efbce97322080de96c2027
- Size of remote file:
- 1.63 GB
- SHA256:
- 4a43d4e18933ed3528e6dd41600970ae8464c25cf453a4119856bd524f3c65fc
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