Instructions to use intelcomp/ipc_level0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use intelcomp/ipc_level0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="intelcomp/ipc_level0")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("intelcomp/ipc_level0") model = AutoModelForSequenceClassification.from_pretrained("intelcomp/ipc_level0", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from intelcomp/ipc_level0: direct link, hf CLI and curl.
- Browser
- Download file 1.42 GB
-
https://huggingface.co/intelcomp/ipc_level0/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://intelcomp/ipc_level0/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/intelcomp/ipc_level0/resolve/main/pytorch_model.bin
1.42 GB
- Xet hash:
- 94c71d202cf17bc6af57a9cafdd84ba3cfd8e9e77eb81fedc2850276ba06ce31
- Size of remote file:
- 1.42 GB
- SHA256:
- e0f179b15fc1ed7e8b57544150935f52c02d380a1ab401567979987615bd3524
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