Instructions to use dbernsohn/roberta-go with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dbernsohn/roberta-go with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="dbernsohn/roberta-go")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("dbernsohn/roberta-go") model = AutoModelForMaskedLM.from_pretrained("dbernsohn/roberta-go", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from dbernsohn/roberta-go: direct link, hf CLI and curl.
- Browser
- Download file 334 MB
-
https://huggingface.co/dbernsohn/roberta-go/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://dbernsohn/roberta-go/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/dbernsohn/roberta-go/resolve/main/flax_model.msgpack
334 MB
- Xet hash:
- 8c53be1ccca2b1014db1694b07a87192934df23758d73ab7df691565c8d55abd
- Size of remote file:
- 334 MB
- SHA256:
- 0071bbfbf47d0f4b1bda838c99313e76fc1d0a86209d15260262972d649a884e
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