Instructions to use fiveflow/roberta-base-spacing with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fiveflow/roberta-base-spacing with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="fiveflow/roberta-base-spacing")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("fiveflow/roberta-base-spacing") model = AutoModelForTokenClassification.from_pretrained("fiveflow/roberta-base-spacing", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from fiveflow/roberta-base-spacing: direct link, hf CLI and curl.
- Browser
- Download file 440 MB
-
https://huggingface.co/fiveflow/roberta-base-spacing/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://fiveflow/roberta-base-spacing/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/fiveflow/roberta-base-spacing/resolve/main/pytorch_model.bin
440 MB
- Xet hash:
- 757dfc4d70dea791ededa45d5feb3b0c64a81c9d5dde561d845fe5ca75b627f9
- Size of remote file:
- 440 MB
- SHA256:
- 1499e7d6de835cb8ef66e187145dc92ebf9e7680318fd0cd9e845e5a4d96b2a0
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