Question Answering
Transformers
PyTorch
TensorBoard
gpt2
Generated from Trainer
text-generation-inference
Instructions to use vaibhav9/GPT2-qa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vaibhav9/GPT2-qa 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="vaibhav9/GPT2-qa")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("vaibhav9/GPT2-qa") model = AutoModelForQuestionAnswering.from_pretrained("vaibhav9/GPT2-qa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from vaibhav9/GPT2-qa: direct link, hf CLI and curl.
- Browser
- Download file 2.11 MB
-
https://huggingface.co/vaibhav9/GPT2-qa/resolve/main/tokenizer.json
- Command line
-
hf download hf://vaibhav9/GPT2-qa/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/vaibhav9/GPT2-qa/resolve/main/tokenizer.json
2.11 MB
File too large to display, you can check the raw version instead.