Instructions to use formermagic/roberta-base-python-1m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use formermagic/roberta-base-python-1m with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="formermagic/roberta-base-python-1m")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("formermagic/roberta-base-python-1m") model = AutoModelForMaskedLM.from_pretrained("formermagic/roberta-base-python-1m", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from formermagic/roberta-base-python-1m: direct link, hf CLI and curl.
- Browser
- Download file 292 MB
-
https://huggingface.co/formermagic/roberta-base-python-1m/resolve/refs%2Fpr%2F1/flax_model.msgpack
- Command line
-
hf download hf://formermagic/roberta-base-python-1m@refs/pr/1/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/formermagic/roberta-base-python-1m/resolve/refs%2Fpr%2F1/flax_model.msgpack
292 MB
- Xet hash:
- 96fd2b845f80663e976cc4ba0df79b9a46eb0c34691a289230c388948dd691d2
- Size of remote file:
- 292 MB
- SHA256:
- 28d2af2347b6ff08dd7cdb7f59eec8215e41946f41b8e8706c2f8fc4b6953783
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