Instructions to use zcbb/hello-huggingface with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zcbb/hello-huggingface with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="zcbb/hello-huggingface")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("zcbb/hello-huggingface") model = AutoModelForSequenceClassification.from_pretrained("zcbb/hello-huggingface", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from zcbb/hello-huggingface: direct link, hf CLI and curl.
- Browser
- Download file 4.86 kB
-
https://huggingface.co/zcbb/hello-huggingface/resolve/main/training_args.bin
- Command line
-
hf download hf://zcbb/hello-huggingface/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/zcbb/hello-huggingface/resolve/main/training_args.bin
4.86 kB
- Xet hash:
- 7d3b926900693f0703a3f93a27224c78d5e17340e1d7666c070b616bf977688d
- Size of remote file:
- 4.86 kB
- SHA256:
- b9ad591684c845796093aac52a4412a88c010eb0f257f34d36303ee6004631ec
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