Instructions to use kaist-ai/langbridge_encoder_tokenizer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kaist-ai/langbridge_encoder_tokenizer with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("kaist-ai/langbridge_encoder_tokenizer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download added_tokens.json from kaist-ai/langbridge_encoder_tokenizer: direct link, hf CLI and curl.
- Browser
- Download file 138 Bytes
-
https://huggingface.co/kaist-ai/langbridge_encoder_tokenizer/resolve/main/added_tokens.json
- Command line
-
hf download hf://kaist-ai/langbridge_encoder_tokenizer/added_tokens.json
-
curl -L -o added_tokens.json https://huggingface.co/kaist-ai/langbridge_encoder_tokenizer/resolve/main/added_tokens.json
138 Bytes
| { | |
| "\t": 250104, | |
| "\n": 250105, | |
| "\u000b": 250107, | |
| "\f": 250100, | |
| "\r": 250103, | |
| " ": 250106, | |
| " ": 250102, | |
| " ": 250101 | |
| } | |