Instructions to use truong1301/my_awesome_qa_model_vifactcheck with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use truong1301/my_awesome_qa_model_vifactcheck with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="truong1301/my_awesome_qa_model_vifactcheck")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("truong1301/my_awesome_qa_model_vifactcheck") model = AutoModelForQuestionAnswering.from_pretrained("truong1301/my_awesome_qa_model_vifactcheck") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0958cadcf97a8d8abb97f3112bbb68630f2b97c45009e0c133698457a1fe9c8c
- Size of remote file:
- 16.3 MB
- SHA256:
- d72f43cffd0dfbeb58d31a9bf13be33ac1c0d7c6691e09b6238d711cf11b6610
路
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.