Instructions to use neuropark/sahajBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use neuropark/sahajBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="neuropark/sahajBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForPreTraining tokenizer = AutoTokenizer.from_pretrained("neuropark/sahajBERT") model = AutoModelForPreTraining.from_pretrained("neuropark/sahajBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download optimizer_state.pt from neuropark/sahajBERT: direct link, hf CLI and curl.
- Browser
- Download file 33.3 MB
-
https://huggingface.co/neuropark/sahajBERT/resolve/main/optimizer_state.pt
- Command line
-
hf download hf://neuropark/sahajBERT/optimizer_state.pt
-
curl -L -o optimizer_state.pt https://huggingface.co/neuropark/sahajBERT/resolve/main/optimizer_state.pt
33.3 MB
- Xet hash:
- 99ae0abe1b6937e0afd5396e9c5719d4d347803d0cb6d5d9dc03ae4885545cbb
- Size of remote file:
- 33.3 MB
- SHA256:
- 40cf0e66f504eec73e229527386be2b14a7132290cf2041f9f3f17970a5f3463
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