Text Classification
Transformers
Safetensors
deberta-v2
multi_label_classification
question-answering
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use saiteki-kai/QA-DeBERTa-v3-large-diff-binary with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use saiteki-kai/QA-DeBERTa-v3-large-diff-binary with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="saiteki-kai/QA-DeBERTa-v3-large-diff-binary")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, DebertaQADiff tokenizer = AutoTokenizer.from_pretrained("saiteki-kai/QA-DeBERTa-v3-large-diff-binary") model = DebertaQADiff.from_pretrained("saiteki-kai/QA-DeBERTa-v3-large-diff-binary", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download special_tokens_map.json from saiteki-kai/QA-DeBERTa-v3-large-diff-binary: direct link, hf CLI and curl.
- Browser
- Download file 286 Bytes
-
https://huggingface.co/saiteki-kai/QA-DeBERTa-v3-large-diff-binary/resolve/main/special_tokens_map.json
- Command line
-
hf download hf://saiteki-kai/QA-DeBERTa-v3-large-diff-binary/special_tokens_map.json
-
curl -L -o special_tokens_map.json https://huggingface.co/saiteki-kai/QA-DeBERTa-v3-large-diff-binary/resolve/main/special_tokens_map.json
286 Bytes
| { | |
| "bos_token": "[CLS]", | |
| "cls_token": "[CLS]", | |
| "eos_token": "[SEP]", | |
| "mask_token": "[MASK]", | |
| "pad_token": "[PAD]", | |
| "sep_token": "[SEP]", | |
| "unk_token": { | |
| "content": "[UNK]", | |
| "lstrip": false, | |
| "normalized": true, | |
| "rstrip": false, | |
| "single_word": false | |
| } | |
| } | |