Text Classification
Transformers
PyTorch
TensorBoard
Safetensors
English
deberta-v2
Generated from Trainer
nlu
intent-classification
Eval Results (legacy)
text-embeddings-inference
Instructions to use cartesinus/mdeberta-v3-base_amazon-massive_intent with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cartesinus/mdeberta-v3-base_amazon-massive_intent with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="cartesinus/mdeberta-v3-base_amazon-massive_intent")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("cartesinus/mdeberta-v3-base_amazon-massive_intent") model = AutoModelForSequenceClassification.from_pretrained("cartesinus/mdeberta-v3-base_amazon-massive_intent", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from cartesinus/mdeberta-v3-base_amazon-massive_intent: direct link, hf CLI and curl.
- Browser
- Download file 399 Bytes
-
https://huggingface.co/cartesinus/mdeberta-v3-base_amazon-massive_intent/resolve/refs%2Fpr%2F2/tokenizer_config.json
- Command line
-
hf download hf://cartesinus/mdeberta-v3-base_amazon-massive_intent@refs/pr/2/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/cartesinus/mdeberta-v3-base_amazon-massive_intent/resolve/refs%2Fpr%2F2/tokenizer_config.json
399 Bytes
| { | |
| "bos_token": "[CLS]", | |
| "cls_token": "[CLS]", | |
| "do_lower_case": false, | |
| "eos_token": "[SEP]", | |
| "mask_token": "[MASK]", | |
| "name_or_path": "microsoft/deberta-v3-base", | |
| "pad_token": "[PAD]", | |
| "sep_token": "[SEP]", | |
| "sp_model_kwargs": {}, | |
| "special_tokens_map_file": null, | |
| "split_by_punct": false, | |
| "tokenizer_class": "DebertaV2Tokenizer", | |
| "unk_token": "[UNK]", | |
| "vocab_type": "spm" | |
| } | |