Instructions to use brao/innox-distilbert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use brao/innox-distilbert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="brao/innox-distilbert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("brao/innox-distilbert") model = AutoModelForTokenClassification.from_pretrained("brao/innox-distilbert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from brao/innox-distilbert: direct link, hf CLI and curl.
- Browser
- Download file 531 MB
-
https://huggingface.co/brao/innox-distilbert/resolve/main/optimizer.pt
- Command line
-
hf download hf://brao/innox-distilbert/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/brao/innox-distilbert/resolve/main/optimizer.pt
531 MB
- Xet hash:
- 1f7c074aebcbe9f5cfccdc7c02ee6eb034f8facbf67a441821ec71144649af51
- Size of remote file:
- 531 MB
- SHA256:
- c2a3ab5ca07ff26760245a26d83625be9d0529dcdacf07c376466542abc42495
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