Instructions to use ChatterjeeLab/FusOn-pLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ChatterjeeLab/FusOn-pLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="ChatterjeeLab/FusOn-pLM")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("ChatterjeeLab/FusOn-pLM") model = AutoModelForMaskedLM.from_pretrained("ChatterjeeLab/FusOn-pLM", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download fuson_plm/data/clustering/mmseqs_full_results.csv from ChatterjeeLab/FusOn-pLM: direct link, hf CLI and curl.
- Browser
- Download file 56 MB
-
https://huggingface.co/ChatterjeeLab/FusOn-pLM/resolve/main/fuson_plm/data/clustering/mmseqs_full_results.csv
- Command line
-
hf download hf://ChatterjeeLab/FusOn-pLM/fuson_plm/data/clustering/mmseqs_full_results.csv
-
curl -L -o mmseqs_full_results.csv https://huggingface.co/ChatterjeeLab/FusOn-pLM/resolve/main/fuson_plm/data/clustering/mmseqs_full_results.csv
56 MB
- Xet hash:
- 9e57b5581ddde8f6a6be69a15791d6b6360a00a84f0317464b1bad9faacd6df0
- Size of remote file:
- 56 MB
- SHA256:
- 8e503a6511f93265a964fd105200a05fa957d9fc2e0edee37dbb3f0b0f55486e
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