Instructions to use macedonizer/hr-roberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use macedonizer/hr-roberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="macedonizer/hr-roberta-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("macedonizer/hr-roberta-base") model = AutoModelForMaskedLM.from_pretrained("macedonizer/hr-roberta-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from macedonizer/hr-roberta-base: direct link, hf CLI and curl.
- Browser
- Download file 334 MB
-
https://huggingface.co/macedonizer/hr-roberta-base/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://macedonizer/hr-roberta-base/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/macedonizer/hr-roberta-base/resolve/main/flax_model.msgpack
334 MB
- Xet hash:
- ddefc430fdd2b7350dec1971649c945b01372619cd9fd2576c484dc13b9888fa
- Size of remote file:
- 334 MB
- SHA256:
- cf15a1a06f1fd4a2805d9964563d20ef76aecd871e98c52fea44a2193587bad2
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