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
Commit History
-
Add evaluation results on the squad_v2 config and validation split of squad_v2
Beep boop, I am a bot from Hugging Face's automatic model evaluator 👋!\ Your model has been evaluated on the squad_v2 config and validation split of the [squad_v2](https://huggingface.co/datasets/squad_v2) dataset by @ob, using the predictions stored [here](https://huggingface.co/datasets/autoevaluate/autoeval-eval-squad_v2-squad_v2-d6c6f4-2395874932).\ Accept this pull request to see the results displayed on the [Hub leaderboard](https://huggingface.co/spaces/autoevaluate/leaderboards?dataset=squad_v2).\ Evaluate your model on more datasets [here](https://huggingface.co/spaces/autoevaluate/model-evaluator?dataset=squad_v2).181a68d
-
update model card README.md
8fb6053 -
Training complete
1be8208 -
Training in progress, epoch 3
00ffaa5 -
Training in progress, epoch 2
44ad968 -
Training in progress, epoch 1
b71af04 -
initial commit
ca0c910