Instructions to use gowitheflow/LASER-cubed-bert-base-unsup with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gowitheflow/LASER-cubed-bert-base-unsup with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("gowitheflow/LASER-cubed-bert-base-unsup") model = AutoModel.from_pretrained("gowitheflow/LASER-cubed-bert-base-unsup", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download 1_Pooling/config.json from gowitheflow/LASER-cubed-bert-base-unsup: direct link, hf CLI and curl.
- Browser
- Download file 190 Bytes
-
https://huggingface.co/gowitheflow/LASER-cubed-bert-base-unsup/resolve/main/1_Pooling/config.json
- Command line
-
hf download hf://gowitheflow/LASER-cubed-bert-base-unsup/1_Pooling/config.json
-
curl -L -o config.json https://huggingface.co/gowitheflow/LASER-cubed-bert-base-unsup/resolve/main/1_Pooling/config.json
190 Bytes
| { | |
| "word_embedding_dimension": 768, | |
| "pooling_mode_cls_token": false, | |
| "pooling_mode_mean_tokens": true, | |
| "pooling_mode_max_tokens": false, | |
| "pooling_mode_mean_sqrt_len_tokens": false | |
| } |