Instructions to use jeniya/BERTOverflow_stackoverflow_github with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jeniya/BERTOverflow_stackoverflow_github with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="jeniya/BERTOverflow_stackoverflow_github")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("jeniya/BERTOverflow_stackoverflow_github") model = AutoModel.from_pretrained("jeniya/BERTOverflow_stackoverflow_github", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from jeniya/BERTOverflow_stackoverflow_github: direct link, hf CLI and curl.
- Browser
- Download file 596 MB
-
https://huggingface.co/jeniya/BERTOverflow_stackoverflow_github/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://jeniya/BERTOverflow_stackoverflow_github/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/jeniya/BERTOverflow_stackoverflow_github/resolve/main/flax_model.msgpack
596 MB
- Xet hash:
- e65f3df34ba7e6ffcb4a52179e6ac59914ef1d4bdd27169b5a5604ca1b486a54
- Size of remote file:
- 596 MB
- SHA256:
- dc67d2f8840da02cb96107344eb8f1b974e02cf0b311d4c6a25ce3688baae781
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