Instructions to use thenlpresearcher/HuggingFaceTB_SmolLM2-360M_StereoDetect_Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use thenlpresearcher/HuggingFaceTB_SmolLM2-360M_StereoDetect_Model with PEFT:
from peft import PeftModel from transformers import AutoModelForSequenceClassification base_model = AutoModelForSequenceClassification.from_pretrained("HuggingFaceTB/SmolLM2-360M") model = PeftModel.from_pretrained(base_model, "thenlpresearcher/HuggingFaceTB_SmolLM2-360M_StereoDetect_Model") - Transformers
How to use thenlpresearcher/HuggingFaceTB_SmolLM2-360M_StereoDetect_Model with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("thenlpresearcher/HuggingFaceTB_SmolLM2-360M_StereoDetect_Model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 75befbdf0a0a80b39439ad55742645b3ac7574a2330cf8a9889c962f67ab7c00
- Size of remote file:
- 5.37 kB
- SHA256:
- 6a14c1086b86d4e0f4a13daf8445cc020efa91805b9555f2f42a111049eae03a
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