Instructions to use JohnLei/50-shot-qaner-s2-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JohnLei/50-shot-qaner-s2-v2 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="JohnLei/50-shot-qaner-s2-v2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("JohnLei/50-shot-qaner-s2-v2") model = AutoModelForQuestionAnswering.from_pretrained("JohnLei/50-shot-qaner-s2-v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from JohnLei/50-shot-qaner-s2-v2: direct link, hf CLI and curl.
- Browser
- Download file 712 kB
-
https://huggingface.co/JohnLei/50-shot-qaner-s2-v2/resolve/main/tokenizer.json
- Command line
-
hf download hf://JohnLei/50-shot-qaner-s2-v2/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/JohnLei/50-shot-qaner-s2-v2/resolve/main/tokenizer.json
712 kB
File too large to display, you can check the raw version instead.