Instructions to use harinib/model_los_removing_layer_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use harinib/model_los_removing_layer_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="harinib/model_los_removing_layer_2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("harinib/model_los_removing_layer_2") model = AutoModelForSequenceClassification.from_pretrained("harinib/model_los_removing_layer_2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from harinib/model_los_removing_layer_2: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/harinib/model_los_removing_layer_2/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://harinib/model_los_removing_layer_2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/harinib/model_los_removing_layer_2/resolve/main/pytorch_model.bin
268 MB
- Xet hash:
- 2c97bc8993ffbc7248dbc037c6560ddf645eece6a3b751753e127bb5b2928829
- Size of remote file:
- 268 MB
- SHA256:
- 76dc7ba74cef11a1a47f4876ad179d6fef3244c3357fb0ecf9f2eb1352099b4d
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