Instructions to use nidhinthomas/AdQuest-when-how-many with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nidhinthomas/AdQuest-when-how-many 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="nidhinthomas/AdQuest-when-how-many")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("nidhinthomas/AdQuest-when-how-many") model = AutoModelForQuestionAnswering.from_pretrained("nidhinthomas/AdQuest-when-how-many", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from nidhinthomas/AdQuest-when-how-many: direct link, hf CLI and curl.
- Browser
- Download file 1.38 kB
-
https://huggingface.co/nidhinthomas/AdQuest-when-how-many/resolve/4fe00adaf46b96a10edad82e0d78240a46406b83/tokenizer_config.json
- Command line
-
hf download hf://nidhinthomas/AdQuest-when-how-many@4fe00adaf46b96a10edad82e0d78240a46406b83/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/nidhinthomas/AdQuest-when-how-many/resolve/4fe00adaf46b96a10edad82e0d78240a46406b83/tokenizer_config.json
1.38 kB
| { | |
| "added_tokens_decoder": { | |
| "0": { | |
| "content": "[PAD]", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "100": { | |
| "content": "[UNK]", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "101": { | |
| "content": "[CLS]", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "102": { | |
| "content": "[SEP]", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "103": { | |
| "content": "[MASK]", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| } | |
| }, | |
| "clean_up_tokenization_spaces": true, | |
| "cls_token": "[CLS]", | |
| "do_lower_case": true, | |
| "mask_token": "[MASK]", | |
| "max_length": 384, | |
| "model_max_length": 512, | |
| "pad_to_multiple_of": null, | |
| "pad_token": "[PAD]", | |
| "pad_token_type_id": 0, | |
| "padding_side": "right", | |
| "sep_token": "[SEP]", | |
| "stride": 128, | |
| "strip_accents": null, | |
| "tokenize_chinese_chars": true, | |
| "tokenizer_class": "ElectraTokenizer", | |
| "truncation_side": "right", | |
| "truncation_strategy": "only_second", | |
| "unk_token": "[UNK]" | |
| } | |