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:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("thenlpresearcher/HuggingFaceTB_SmolLM2-360M_StereoDetect_Model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from thenlpresearcher/HuggingFaceTB_SmolLM2-360M_StereoDetect_Model: direct link, hf CLI and curl.
- Browser
- Download file 3.52 MB
-
https://huggingface.co/thenlpresearcher/HuggingFaceTB_SmolLM2-360M_StereoDetect_Model/resolve/main/tokenizer.json
- Command line
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hf download hf://thenlpresearcher/HuggingFaceTB_SmolLM2-360M_StereoDetect_Model/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/thenlpresearcher/HuggingFaceTB_SmolLM2-360M_StereoDetect_Model/resolve/main/tokenizer.json
3.52 MB
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