Instructions to use navteca/quora-roberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use navteca/quora-roberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="navteca/quora-roberta-base")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("navteca/quora-roberta-base") model = AutoModelForSequenceClassification.from_pretrained("navteca/quora-roberta-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from navteca/quora-roberta-base: direct link, hf CLI and curl.
- Browser
- Download file 150 Bytes
-
https://huggingface.co/navteca/quora-roberta-base/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://navteca/quora-roberta-base/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/navteca/quora-roberta-base/resolve/main/tokenizer_config.json
150 Bytes
| { | |
| "do_lower_case": false, | |
| "full_tokenizer_file": null, | |
| "model_max_length": 512, | |
| "special_tokens_map_file": "special_tokens_map.json" | |
| } |