Instructions to use nbroad/splinter-base-squad2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nbroad/splinter-base-squad2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="nbroad/splinter-base-squad2")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("nbroad/splinter-base-squad2") model = AutoModelForQuestionAnswering.from_pretrained("nbroad/splinter-base-squad2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 630 Bytes
128ad72 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | {
"additional_special_tokens": [
"[QUESTION]"
],
"cls_token": "[CLS]",
"do_basic_tokenize": true,
"do_lower_case": false,
"mask_token": "[MASK]",
"model_max_length": 512,
"name_or_path": "tau/splinter-base-qass",
"never_split": null,
"pad_token": "[PAD]",
"sep_token": "[SEP]",
"special_tokens_map_file": "/home/.cache/huggingface/transformers/4abdf987baedc3cc34df313a86725615a89b36b3b69631703c5c99fd165fcb6b.5f8d8adb4106c43ee43d2bbbdf22053095b63cf98e866c0164335424931f338c",
"strip_accents": null,
"tokenize_chinese_chars": true,
"tokenizer_class": "SplinterTokenizer",
"unk_token": "[UNK]"
}
|