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 preprocessed_data.json from whitedevil0089devil/roberta_base: direct link, hf CLI and curl.
- Browser
- Download file 138 MB
-
https://huggingface.co/whitedevil0089devil/roberta_base/resolve/6ac6fe1f0cdfe67b1c192541dbad7562aa7b3abd/preprocessed_data.json
- Command line
-
hf download hf://whitedevil0089devil/roberta_base@6ac6fe1f0cdfe67b1c192541dbad7562aa7b3abd/preprocessed_data.json
-
curl -L -o preprocessed_data.json https://huggingface.co/whitedevil0089devil/roberta_base/resolve/6ac6fe1f0cdfe67b1c192541dbad7562aa7b3abd/preprocessed_data.json
138 MB
- Xet hash:
- f2c0ccdcfbafed04d4aac4725c732b322452283c32c1c62c1cf93e112d363cd4
- Size of remote file:
- 138 MB
- SHA256:
- d0746358a09762ed1dc54f6177fbb5aad408b1e211169bd62ecd530ffb22ff81
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.