Instructions to use akhil2808/EPICS-PROJECT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use akhil2808/EPICS-PROJECT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="akhil2808/EPICS-PROJECT")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("akhil2808/EPICS-PROJECT") model = AutoModelForSequenceClassification.from_pretrained("akhil2808/EPICS-PROJECT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 59464cabc3b62db1b69668e1be1c216a1b218497acddad67f81d511ba661ce0a
- Size of remote file:
- 438 MB
- SHA256:
- 074447870d19945dd666ac646446c707d02d9a9362452067407231f329c52014
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