Instructions to use SRDdev/QABERT-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SRDdev/QABERT-small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="SRDdev/QABERT-small")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("SRDdev/QABERT-small") model = AutoModelForQuestionAnswering.from_pretrained("SRDdev/QABERT-small", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from SRDdev/QABERT-small: direct link, hf CLI and curl.
- Browser
- Download file 712 kB
-
https://huggingface.co/SRDdev/QABERT-small/resolve/main/tokenizer.json
- Command line
-
hf download hf://SRDdev/QABERT-small/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/SRDdev/QABERT-small/resolve/main/tokenizer.json
712 kB
File too large to display, you can check the raw version instead.