Instructions to use Jose-Ribeir/stt_Huggin_face_tech_new_data with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jose-Ribeir/stt_Huggin_face_tech_new_data with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("question-answering", model="Jose-Ribeir/stt_Huggin_face_tech_new_data")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("Jose-Ribeir/stt_Huggin_face_tech_new_data") model = AutoModelForQuestionAnswering.from_pretrained("Jose-Ribeir/stt_Huggin_face_tech_new_data", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download special_tokens_map.json from Jose-Ribeir/stt_Huggin_face_tech_new_data: direct link, hf CLI and curl.
- Browser
- Download file 132 Bytes
-
https://huggingface.co/Jose-Ribeir/stt_Huggin_face_tech_new_data/resolve/main/special_tokens_map.json
- Command line
-
hf download hf://Jose-Ribeir/stt_Huggin_face_tech_new_data/special_tokens_map.json
-
curl -L -o special_tokens_map.json https://huggingface.co/Jose-Ribeir/stt_Huggin_face_tech_new_data/resolve/main/special_tokens_map.json
132 Bytes
| { | |
| "cls_token": "[CLS]", | |
| "mask_token": "[MASK]", | |
| "pad_token": "[PAD]", | |
| "sep_token": "[SEP]", | |
| "unk_token": "[UNK]" | |
| } | |