Instructions to use Chillyblast/Roberta_Question_Answer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Chillyblast/Roberta_Question_Answer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Chillyblast/Roberta_Question_Answer")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Chillyblast/Roberta_Question_Answer") model = AutoModelForSequenceClassification.from_pretrained("Chillyblast/Roberta_Question_Answer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from Chillyblast/Roberta_Question_Answer: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/Chillyblast/Roberta_Question_Answer/resolve/main/model.safetensors
- Command line
-
hf download hf://Chillyblast/Roberta_Question_Answer/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/Chillyblast/Roberta_Question_Answer/resolve/main/model.safetensors
499 MB
- Xet hash:
- 7b6c3aa854692d2c66f1ae3faaece27dd27f2d1839172b16f279313feaf0b227
- Size of remote file:
- 499 MB
- SHA256:
- 98820826d7e4c736a27f99e764d303793f175ea33f86a5a4c16ad365ce7ed2e6
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.