Instructions to use harinib/model_los_removing_layer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use harinib/model_los_removing_layer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="harinib/model_los_removing_layer")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("harinib/model_los_removing_layer") model = AutoModelForSequenceClassification.from_pretrained("harinib/model_los_removing_layer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from harinib/model_los_removing_layer: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/harinib/model_los_removing_layer/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://harinib/model_los_removing_layer/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/harinib/model_los_removing_layer/resolve/main/pytorch_model.bin
268 MB
- Xet hash:
- 89b27f33e2a207494ab261f132ae37837fdfe3daece274891feadb674ac822c4
- Size of remote file:
- 268 MB
- SHA256:
- 7cf7dd5efb573f8146783b1a73dca96eacc1b11eab96717af0713cf9cf89e007
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