Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use dflcmu/JQED_QA_question_classifer_final with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dflcmu/JQED_QA_question_classifer_final with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dflcmu/JQED_QA_question_classifer_final")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dflcmu/JQED_QA_question_classifer_final") model = AutoModelForSequenceClassification.from_pretrained("dflcmu/JQED_QA_question_classifer_final", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from dflcmu/JQED_QA_question_classifer_final: direct link, hf CLI and curl.
- Browser
- Download file 3.58 kB
-
https://huggingface.co/dflcmu/JQED_QA_question_classifer_final/resolve/main/training_args.bin
- Command line
-
hf download hf://dflcmu/JQED_QA_question_classifer_final/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/dflcmu/JQED_QA_question_classifer_final/resolve/main/training_args.bin
3.58 kB
- Xet hash:
- 6fb3a5f58ebe7fee05e3a6dde14458d0e66f007aeb59defdfbced91c6d2f3e99
- Size of remote file:
- 3.58 kB
- SHA256:
- 28cd7c7be7ab77c7aed5aa46ae94443f9992c1e38d3dd5907d173d459863fa9d
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