Instructions to use sohamtiwari3120/checkpoint-16500 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sohamtiwari3120/checkpoint-16500 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="sohamtiwari3120/checkpoint-16500")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("sohamtiwari3120/checkpoint-16500") model = AutoModelForQuestionAnswering.from_pretrained("sohamtiwari3120/checkpoint-16500", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b30924ac551e6f8f992160e25e55a1ec5c1a1af94e6a2ea0d9221a2131995f6d
- Size of remote file:
- 667 MB
- SHA256:
- b991e7ca7438b596d341307f6d6b3a5198cb498635380ecf7610df898104af7a
路
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