Text Classification
PyTorch
Transformers
English
Transformers
bert
nlp
argilla
text-embeddings-inference
Instructions to use plaguss/test_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use plaguss/test_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="plaguss/test_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("plaguss/test_model") model = AutoModelForSequenceClassification.from_pretrained("plaguss/test_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download special_tokens_map.json from plaguss/test_model: direct link, hf CLI and curl.
- Browser
- Download file 125 Bytes
-
https://huggingface.co/plaguss/test_model/resolve/b3ea96a522a2bf8847ba0734eb7d4031fc51730b/special_tokens_map.json
- Command line
-
hf download hf://plaguss/test_model@b3ea96a522a2bf8847ba0734eb7d4031fc51730b/special_tokens_map.json
-
curl -L -o special_tokens_map.json https://huggingface.co/plaguss/test_model/resolve/b3ea96a522a2bf8847ba0734eb7d4031fc51730b/special_tokens_map.json
125 Bytes
| { | |
| "cls_token": "[CLS]", | |
| "mask_token": "[MASK]", | |
| "pad_token": "[PAD]", | |
| "sep_token": "[SEP]", | |
| "unk_token": "[UNK]" | |
| } | |