Question Answering
Transformers
PyTorch
TensorBoard
electra
Generated from Trainer
Eval Results (legacy)
Instructions to use mlxen/electra-smallcase-squad with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mlxen/electra-smallcase-squad with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("question-answering", model="mlxen/electra-smallcase-squad")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("mlxen/electra-smallcase-squad") model = AutoModelForQuestionAnswering.from_pretrained("mlxen/electra-smallcase-squad", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from mlxen/electra-smallcase-squad: direct link, hf CLI and curl.
- Browser
- Download file 711 kB
-
https://huggingface.co/mlxen/electra-smallcase-squad/resolve/refs%2Fpr%2F1/tokenizer.json
- Command line
-
hf download hf://mlxen/electra-smallcase-squad@refs/pr/1/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/mlxen/electra-smallcase-squad/resolve/refs%2Fpr%2F1/tokenizer.json
711 kB
File too large to display, you can check the raw version instead.