Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use gerbejon/digilog-eform-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gerbejon/digilog-eform-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="gerbejon/digilog-eform-classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("gerbejon/digilog-eform-classifier") model = AutoModelForSequenceClassification.from_pretrained("gerbejon/digilog-eform-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-2000/scheduler.pt from gerbejon/digilog-eform-classifier: direct link, hf CLI and curl.
- Browser
- Download file 1.06 kB
-
https://huggingface.co/gerbejon/digilog-eform-classifier/resolve/main/checkpoint-2000/scheduler.pt
- Command line
-
hf download hf://gerbejon/digilog-eform-classifier/checkpoint-2000/scheduler.pt
-
curl -L -o scheduler.pt https://huggingface.co/gerbejon/digilog-eform-classifier/resolve/main/checkpoint-2000/scheduler.pt
1.06 kB
- Xet hash:
- c63bd375f71f7de8c8e98615843dd2ae2e635e65d7d8cf43c0ef922f9f812e3c
- Size of remote file:
- 1.06 kB
- SHA256:
- c85bada4ac12da9bc05925afb9a1f6da25e734c2de7a5b86454e2f3562456b43
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.