Instructions to use mrm8488/bert-tiny-3-finetuned-squadv2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mrm8488/bert-tiny-3-finetuned-squadv2 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="mrm8488/bert-tiny-3-finetuned-squadv2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("mrm8488/bert-tiny-3-finetuned-squadv2") model = AutoModelForQuestionAnswering.from_pretrained("mrm8488/bert-tiny-3-finetuned-squadv2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
upload flax model
6ad3c80 -
allow flax
42cf4d7
-
Update config.json
6c84974
-
Update config.json
8473e6c
-
Update scheduler.pt
f65c62d -
Update vocab.txt
96f1332 -
Update special_tokens_map.json
6d1aea8 -
Update tokenizer_config.json
cc7dcbc -
Update pytorch_model.bin
ce3d699 -
Update training_args.bin
294924c -
Update optimizer.pt
ce4f68d -
Update config.json
98dd6de -
initial commit
49231ad