Instructions to use intelcomp/ipc_level1_A with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use intelcomp/ipc_level1_A with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="intelcomp/ipc_level1_A")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("intelcomp/ipc_level1_A") model = AutoModelForSequenceClassification.from_pretrained("intelcomp/ipc_level1_A", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from intelcomp/ipc_level1_A: direct link, hf CLI and curl.
- Browser
- Download file 2.74 kB
-
https://huggingface.co/intelcomp/ipc_level1_A/resolve/main/training_args.bin
- Command line
-
hf download hf://intelcomp/ipc_level1_A/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/intelcomp/ipc_level1_A/resolve/main/training_args.bin
2.74 kB
- Xet hash:
- 279aa223b5adcbf175cd3ad74bd6c341780cb4d769487b4438222687b14fec11
- Size of remote file:
- 2.74 kB
- SHA256:
- e2d7fbce1bd319d6108183732e817fe542839a983283ece3b1f04d38f988a086
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