Instructions to use bumblebee-testing/tiny-random-GemmaForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bumblebee-testing/tiny-random-GemmaForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="bumblebee-testing/tiny-random-GemmaForSequenceClassification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("bumblebee-testing/tiny-random-GemmaForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("bumblebee-testing/tiny-random-GemmaForSequenceClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from bumblebee-testing/tiny-random-GemmaForSequenceClassification: direct link, hf CLI and curl.
- Browser
- Download file 187 kB
-
https://huggingface.co/bumblebee-testing/tiny-random-GemmaForSequenceClassification/resolve/main/model.safetensors
- Command line
-
hf download hf://bumblebee-testing/tiny-random-GemmaForSequenceClassification/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/bumblebee-testing/tiny-random-GemmaForSequenceClassification/resolve/main/model.safetensors
187 kB
- Xet hash:
- 6a641c27ae7290b72f149dcbf7d5a882e6298556aa450787fc64043d6758d0da
- Size of remote file:
- 187 kB
- SHA256:
- a796748bd2a60712daf1a121b749f486873c24ff3aea5f07ce70a3e9c53a0960
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