Instructions to use intelcomp/ipc_level1_E with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use intelcomp/ipc_level1_E with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="intelcomp/ipc_level1_E")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("intelcomp/ipc_level1_E") model = AutoModelForSequenceClassification.from_pretrained("intelcomp/ipc_level1_E", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from intelcomp/ipc_level1_E: direct link, hf CLI and curl.
- Browser
- Download file 2.74 kB
-
https://huggingface.co/intelcomp/ipc_level1_E/resolve/main/training_args.bin
- Command line
-
hf download hf://intelcomp/ipc_level1_E/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/intelcomp/ipc_level1_E/resolve/main/training_args.bin
2.74 kB
- Xet hash:
- 4889c9c1d78e47cdfdf8c8c14386157f548f060db315cb220f3e4596676d24fc
- Size of remote file:
- 2.74 kB
- SHA256:
- 198b3e365aece9bde9345a57c8dfc9f4eac304b98376c399d196be2d126f6304
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