Instructions to use intelcomp/ipc_level1_G with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use intelcomp/ipc_level1_G with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="intelcomp/ipc_level1_G")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("intelcomp/ipc_level1_G") model = AutoModelForSequenceClassification.from_pretrained("intelcomp/ipc_level1_G", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from intelcomp/ipc_level1_G: direct link, hf CLI and curl.
- Browser
- Download file 1.42 GB
-
https://huggingface.co/intelcomp/ipc_level1_G/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://intelcomp/ipc_level1_G/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/intelcomp/ipc_level1_G/resolve/main/pytorch_model.bin
1.42 GB
- Xet hash:
- 773286c65bcb22599701451ebb197ed3f6b65a252218a62137661328637c0109
- Size of remote file:
- 1.42 GB
- SHA256:
- da3a92db5bc9dfb55bf0b56cba33d7c91c72b198598f9819fbaa6ed580903b7b
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