Instructions to use justpyschitry/autotrain-Wikipeida_Article_Classifier_by_Chap-1022634735 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use justpyschitry/autotrain-Wikipeida_Article_Classifier_by_Chap-1022634735 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="justpyschitry/autotrain-Wikipeida_Article_Classifier_by_Chap-1022634735")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("justpyschitry/autotrain-Wikipeida_Article_Classifier_by_Chap-1022634735") model = AutoModelForSequenceClassification.from_pretrained("justpyschitry/autotrain-Wikipeida_Article_Classifier_by_Chap-1022634735", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download sample_input.pkl from justpyschitry/autotrain-Wikipeida_Article_Classifier_by_Chap-1022634735: direct link, hf CLI and curl.
- Browser
- Download file 4.38 kB
-
https://huggingface.co/justpyschitry/autotrain-Wikipeida_Article_Classifier_by_Chap-1022634735/resolve/refs%2Fpr%2F1/sample_input.pkl
- Command line
-
hf download hf://justpyschitry/autotrain-Wikipeida_Article_Classifier_by_Chap-1022634735@refs/pr/1/sample_input.pkl
-
curl -L -o sample_input.pkl https://huggingface.co/justpyschitry/autotrain-Wikipeida_Article_Classifier_by_Chap-1022634735/resolve/refs%2Fpr%2F1/sample_input.pkl
4.38 kB
- Xet hash:
- c6be7dd9023b3365c70eb083c7c67f65625617f2f284a90e3d8c06ab7ca345fb
- Size of remote file:
- 4.38 kB
- SHA256:
- 3febec0bca076249a423a66f54312182ec8b9ad8a95afe5765a7bf65442d2151
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