Instructions to use harpreetmann/stack_exc_multilabel_base_class_head with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use harpreetmann/stack_exc_multilabel_base_class_head with PEFT:
from peft import PeftModel from transformers import AutoModelForSequenceClassification base_model = AutoModelForSequenceClassification.from_pretrained("google/gemma-2-2b") model = PeftModel.from_pretrained(base_model, "harpreetmann/stack_exc_multilabel_base_class_head") - Transformers
How to use harpreetmann/stack_exc_multilabel_base_class_head with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("harpreetmann/stack_exc_multilabel_base_class_head", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from harpreetmann/stack_exc_multilabel_base_class_head: direct link, hf CLI and curl.
- Browser
- Download file 1.33 GB
-
https://huggingface.co/harpreetmann/stack_exc_multilabel_base_class_head/resolve/main/optimizer.pt
- Command line
-
hf download hf://harpreetmann/stack_exc_multilabel_base_class_head/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/harpreetmann/stack_exc_multilabel_base_class_head/resolve/main/optimizer.pt
1.33 GB
- Xet hash:
- 0005c830aaf9ace636227d071a7031ae95edf2d4728a5da86aaa8b33de82a0bc
- Size of remote file:
- 1.33 GB
- SHA256:
- 41d0361ec4bc08a19f1f75ed21cc943b461047f3492c514b9a22136f10a08854
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