Instructions to use ruyadisk/span_selection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ruyadisk/span_selection 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="ruyadisk/span_selection")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("ruyadisk/span_selection") model = AutoModelForQuestionAnswering.from_pretrained("ruyadisk/span_selection", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download added_tokens.json from ruyadisk/span_selection: direct link, hf CLI and curl.
- Browser
- Download file 82 Bytes
-
https://huggingface.co/ruyadisk/span_selection/resolve/main/added_tokens.json
- Command line
-
hf download hf://ruyadisk/span_selection/added_tokens.json
-
curl -L -o added_tokens.json https://huggingface.co/ruyadisk/span_selection/resolve/main/added_tokens.json
82 Bytes
| { | |
| "[CLS]": 101, | |
| "[MASK]": 103, | |
| "[PAD]": 0, | |
| "[SEP]": 102, | |
| "[UNK]": 100 | |
| } | |