Instructions to use srcocotero/tiny-bert-qa-es with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use srcocotero/tiny-bert-qa-es 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="srcocotero/tiny-bert-qa-es")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("srcocotero/tiny-bert-qa-es") model = AutoModelForQuestionAnswering.from_pretrained("srcocotero/tiny-bert-qa-es", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from srcocotero/tiny-bert-qa-es: direct link, hf CLI and curl.
- Browser
- Download file 2.46 MB
-
https://huggingface.co/srcocotero/tiny-bert-qa-es/resolve/main/tokenizer.json
- Command line
-
hf download hf://srcocotero/tiny-bert-qa-es/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/srcocotero/tiny-bert-qa-es/resolve/main/tokenizer.json
2.46 MB
File too large to display, you can check the raw version instead.