Feature Extraction
Transformers
PyTorch
English
bert
biomedical
bionlp
entity linking
embedding
text-embeddings-inference
Instructions to use andorei/gebert_eng_graphsage with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use andorei/gebert_eng_graphsage with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="andorei/gebert_eng_graphsage")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("andorei/gebert_eng_graphsage") model = AutoModel.from_pretrained("andorei/gebert_eng_graphsage", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c08e88cc347bdaed824c78708d1ba3960e0038df8284e1215f056f74e5a53156
- Size of remote file:
- 438 MB
- SHA256:
- dcf3ddfd679cae8fa571010c74c6659c83d577348d07ce6493fd4cfab7c69811
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