Instructions to use Extrabass/checkpoint with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Extrabass/checkpoint with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Extrabass/checkpoint")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Extrabass/checkpoint") model = AutoModelForSequenceClassification.from_pretrained("Extrabass/checkpoint", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from Extrabass/checkpoint: direct link, hf CLI and curl.
- Browser
- Download file 409 MB
-
https://huggingface.co/Extrabass/checkpoint/resolve/main/model.safetensors
- Command line
-
hf download hf://Extrabass/checkpoint/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/Extrabass/checkpoint/resolve/main/model.safetensors
409 MB
- Xet hash:
- 770e1ccf7f59a37af420c61d6a5680c38f896e0480dc1b2445719fc89bb1b678
- Size of remote file:
- 409 MB
- SHA256:
- d375ad6dd0e3ef43788d62b3fd04ec76ccb67c9c15239c883947b0f68e75e3ec
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