Instructions to use mrm8488/RoBasquERTa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mrm8488/RoBasquERTa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="mrm8488/RoBasquERTa")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("mrm8488/RoBasquERTa") model = AutoModelForMaskedLM.from_pretrained("mrm8488/RoBasquERTa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from mrm8488/RoBasquERTa: direct link, hf CLI and curl.
- Browser
- Download file 334 MB
-
https://huggingface.co/mrm8488/RoBasquERTa/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://mrm8488/RoBasquERTa/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/mrm8488/RoBasquERTa/resolve/main/flax_model.msgpack
334 MB
- Xet hash:
- 46aece9e687b6f668f22c7309a8a460a075986c6d3713fce63899715ff384782
- Size of remote file:
- 334 MB
- SHA256:
- 104aeb4c63a5cf3bc2acfcb2344f5a0ee4e79afd4b30a3a78a0d108736a9523a
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