Text Classification
Transformers
Safetensors
PyTorch
English
roberta
question-answering
text-embeddings-inference
Instructions to use whitedevil0089devil/roberta_base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use whitedevil0089devil/roberta_base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="whitedevil0089devil/roberta_base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("whitedevil0089devil/roberta_base") model = AutoModelForSequenceClassification.from_pretrained("whitedevil0089devil/roberta_base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download answer_mapping.json from whitedevil0089devil/roberta_base: direct link, hf CLI and curl.
- Browser
- Download file 289 MB
-
https://huggingface.co/whitedevil0089devil/roberta_base/resolve/6ac6fe1f0cdfe67b1c192541dbad7562aa7b3abd/answer_mapping.json
- Command line
-
hf download hf://whitedevil0089devil/roberta_base@6ac6fe1f0cdfe67b1c192541dbad7562aa7b3abd/answer_mapping.json
-
curl -L -o answer_mapping.json https://huggingface.co/whitedevil0089devil/roberta_base/resolve/6ac6fe1f0cdfe67b1c192541dbad7562aa7b3abd/answer_mapping.json
289 MB
- Xet hash:
- 5b264bec9e0820bc8838f5d1b342f63dfd1ca7b62ef38080c631a940b67b4353
- Size of remote file:
- 289 MB
- SHA256:
- 24b45f44d90a34b79a5bc6beda9fc06ae70fa315e3a72abe19853515b017fff7
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