Instructions to use dbernsohn/roberta-python with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dbernsohn/roberta-python with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="dbernsohn/roberta-python")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("dbernsohn/roberta-python") model = AutoModelForMaskedLM.from_pretrained("dbernsohn/roberta-python", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from dbernsohn/roberta-python: direct link, hf CLI and curl.
- Browser
- Download file 334 MB
-
https://huggingface.co/dbernsohn/roberta-python/resolve/refs%2Fpr%2F1/flax_model.msgpack
- Command line
-
hf download hf://dbernsohn/roberta-python@refs/pr/1/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/dbernsohn/roberta-python/resolve/refs%2Fpr%2F1/flax_model.msgpack
334 MB
- Xet hash:
- 267d14a27df3217798b49edb0b4a10fd4cd93749c63d55dedb83a914aa021dbd
- Size of remote file:
- 334 MB
- SHA256:
- eb18504feeb154a98a46c61dfd876ff09476fe2104a99e2a9cf26c9f2a07b56b
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