Instructions to use MadhurJindalWorkMail/autonlp-Gibb-Detect-515314387 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MadhurJindalWorkMail/autonlp-Gibb-Detect-515314387 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="MadhurJindalWorkMail/autonlp-Gibb-Detect-515314387")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MadhurJindalWorkMail/autonlp-Gibb-Detect-515314387") model = AutoModelForSequenceClassification.from_pretrained("MadhurJindalWorkMail/autonlp-Gibb-Detect-515314387", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from MadhurJindalWorkMail/autonlp-Gibb-Detect-515314387: direct link, hf CLI and curl.
- Browser
- Download file 1.34 GB
-
https://huggingface.co/MadhurJindalWorkMail/autonlp-Gibb-Detect-515314387/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://MadhurJindalWorkMail/autonlp-Gibb-Detect-515314387/pytorch_model.bin
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curl -L -o pytorch_model.bin https://huggingface.co/MadhurJindalWorkMail/autonlp-Gibb-Detect-515314387/resolve/main/pytorch_model.bin
1.34 GB
- Xet hash:
- 26d880026e70de3e9c617443ea961cc487010dbada990da6a834835bcefa8b7d
- Size of remote file:
- 1.34 GB
- SHA256:
- 612dea3861ba427a8e30e1982877d43bf3891a11052e91dadf2e76d3b2268e2e
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