Feature Extraction
Transformers
Safetensors
English
bert
contrastive-learning
embeddings
political-science
social-groups
clustering
text-embeddings-inference
Instructions to use maxwlnd/cl_mention_embedding with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use maxwlnd/cl_mention_embedding with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="maxwlnd/cl_mention_embedding")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("maxwlnd/cl_mention_embedding", dtype="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "cls_token": "[CLS]", | |
| "mask_token": "[MASK]", | |
| "pad_token": "[PAD]", | |
| "sep_token": "[SEP]", | |
| "unk_token": "[UNK]" | |
| } | |