Instructions to use gargam/roberta-base-crest with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gargam/roberta-base-crest with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="gargam/roberta-base-crest")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("gargam/roberta-base-crest") model = AutoModelForSequenceClassification.from_pretrained("gargam/roberta-base-crest", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from gargam/roberta-base-crest: direct link, hf CLI and curl.
- Browser
- Download file 270 Bytes
-
https://huggingface.co/gargam/roberta-base-crest/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://gargam/roberta-base-crest/tokenizer_config.json
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curl -L -o tokenizer_config.json https://huggingface.co/gargam/roberta-base-crest/resolve/main/tokenizer_config.json
270 Bytes
| {"model_max_length": 512, "do_lower_case": false, "special_tokens_map_file": "/root/.cache/torch/transformers/dbacf7ddbc6fa136984a61956e7345033710fdf6a384ed806077d2a56254d507.01d47f83d2e88283cc7f6be55eaef5d08d20297fc3bc1c1618ac15c35d1b97dd", "full_tokenizer_file": null} |