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/raw_data/FOdb_SD5.csv from ChatterjeeLab/FusOn-pLM: direct link, hf CLI and curl.
- Browser
- Download file 19.3 kB
-
https://huggingface.co/ChatterjeeLab/FusOn-pLM/resolve/refs%2Fpr%2F1/fuson_plm/data/raw_data/FOdb_SD5.csv
- Command line
-
hf download hf://ChatterjeeLab/FusOn-pLM@refs/pr/1/fuson_plm/data/raw_data/FOdb_SD5.csv
-
curl -L -o FOdb_SD5.csv https://huggingface.co/ChatterjeeLab/FusOn-pLM/resolve/refs%2Fpr%2F1/fuson_plm/data/raw_data/FOdb_SD5.csv
19.3 kB
- Xet hash:
- ae9c758c7f5ae05c6cbb3c398d29b4173bfcb1ad5d0391466d76d68a92e5ccee
- Size of remote file:
- 19.3 kB
- SHA256:
- 4b4fae3b8ab9661500ac34dc5e96069f76118f79ceac8e101d5361fe5e46d4b4
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