Instructions to use harikp20/hkp24 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use harikp20/hkp24 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="harikp20/hkp24")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("harikp20/hkp24") model = AutoModelForQuestionAnswering.from_pretrained("harikp20/hkp24", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- be2372781c1a462c3096b3fb9a08a5224b33788c2a0f787e420116aa5090e883
- Size of remote file:
- 265 MB
- SHA256:
- f56d405f8d5cff6e502616024ffbce5300dcdf57b5d36164522c08305b4a660d
路
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