Instructions to use scaleszw/roberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use scaleszw/roberta-base with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("question-answering", model="scaleszw/roberta-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("scaleszw/roberta-base") model = AutoModelForQuestionAnswering.from_pretrained("scaleszw/roberta-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from scaleszw/roberta-base: direct link, hf CLI and curl.
- Browser
- Download file 17.1 MB
-
https://huggingface.co/scaleszw/roberta-base/resolve/main/tokenizer.json
- Command line
-
hf download hf://scaleszw/roberta-base/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/scaleszw/roberta-base/resolve/main/tokenizer.json
17.1 MB
- Xet hash:
- dfad33006b656eb0d185691d54eabd734e9859033aa38002e6932c474652d73d
- Size of remote file:
- 17.1 MB
- SHA256:
- e9092d8b5989337626af7001a7a97b88471e2da7c59dce83aba82a0ef90cad1f
路
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