Instructions to use phosseini/atomic-bert-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use phosseini/atomic-bert-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="phosseini/atomic-bert-large")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("phosseini/atomic-bert-large") model = AutoModel.from_pretrained("phosseini/atomic-bert-large") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5d7dc39b342adf4253a3f50029d2d9ee3d8978fa283afb13ac17b5186ec1004f
- Size of remote file:
- 3.06 kB
- SHA256:
- b941f2f11236708ff04aa92903da96ac107c4ab7c4951efc9fb1f142a64b3d43
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