Instructions to use privacy-tech-lab/MultitaskBaseModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use privacy-tech-lab/MultitaskBaseModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="privacy-tech-lab/MultitaskBaseModel")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("privacy-tech-lab/MultitaskBaseModel") model = AutoModelForSequenceClassification.from_pretrained("privacy-tech-lab/MultitaskBaseModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from privacy-tech-lab/MultitaskBaseModel: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/privacy-tech-lab/MultitaskBaseModel/resolve/main/model.safetensors
- Command line
-
hf download hf://privacy-tech-lab/MultitaskBaseModel/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/privacy-tech-lab/MultitaskBaseModel/resolve/main/model.safetensors
438 MB
- Xet hash:
- c203eb5e1c376a3b0d42f5523b2bae62c9e17283bbde8449d4fdf4c8b3b874f3
- Size of remote file:
- 438 MB
- SHA256:
- 17049ef13d68fa5b289295d5bf0f8f90e6aafc3749959452d87398e089e5373d
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