Instructions to use comacrae/roberta-edav3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use comacrae/roberta-edav3 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="comacrae/roberta-edav3")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("comacrae/roberta-edav3") model = AutoModelForQuestionAnswering.from_pretrained("comacrae/roberta-edav3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from comacrae/roberta-edav3: direct link, hf CLI and curl.
- Browser
- Download file 496 MB
-
https://huggingface.co/comacrae/roberta-edav3/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://comacrae/roberta-edav3/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/comacrae/roberta-edav3/resolve/main/pytorch_model.bin
496 MB
- Xet hash:
- acbab884b552ec1073a9877be4b73b983ebac02a83c8b6f461d0b01eabae4a5f
- Size of remote file:
- 496 MB
- SHA256:
- 8da16b4e312b54b7f6b267dda4d68fed90b8c42c92fe241930d86dfb4dc48c32
路
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