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")# pip install -U transformers accelerate # 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 pytorch_model.bin 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/pytorch_model.bin
- Command line
-
hf download hf://formermagic/roberta-base-python-1m@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/formermagic/roberta-base-python-1m/resolve/refs%2Fpr%2F1/pytorch_model.bin
292 MB
- Xet hash:
- fc374cc5e5adeb64acc8e2bc03bbb26c6c8d2063979bf18b315c090ccafb0fa2
- Size of remote file:
- 292 MB
- SHA256:
- 5310e88e1d40230ad9058160e496cc1694edf3f93a49f493da07bd43ce1600eb
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