Instructions to use dicta-il/dictabert-tiny-parse with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dicta-il/dictabert-tiny-parse with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="dicta-il/dictabert-tiny-parse", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("dicta-il/dictabert-tiny-parse", trust_remote_code=True) model = AutoModel.from_pretrained("dicta-il/dictabert-tiny-parse", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download special_tokens_map.json from dicta-il/dictabert-tiny-parse: direct link, hf CLI and curl.
- Browser
- Download file 695 Bytes
-
https://huggingface.co/dicta-il/dictabert-tiny-parse/resolve/main/special_tokens_map.json
- Command line
-
hf download hf://dicta-il/dictabert-tiny-parse/special_tokens_map.json
-
curl -L -o special_tokens_map.json https://huggingface.co/dicta-il/dictabert-tiny-parse/resolve/main/special_tokens_map.json
695 Bytes
| { | |
| "cls_token": { | |
| "content": "[CLS]", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false | |
| }, | |
| "mask_token": { | |
| "content": "[MASK]", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false | |
| }, | |
| "pad_token": { | |
| "content": "[PAD]", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false | |
| }, | |
| "sep_token": { | |
| "content": "[SEP]", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false | |
| }, | |
| "unk_token": { | |
| "content": "[UNK]", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false | |
| } | |
| } | |