Instructions to use Unmand/business_unit_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Unmand/business_unit_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Unmand/business_unit_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Unmand/business_unit_model") model = AutoModelForSequenceClassification.from_pretrained("Unmand/business_unit_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Unmand/business_unit_model: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/Unmand/business_unit_model/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Unmand/business_unit_model/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Unmand/business_unit_model/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 48db6699b72ad3cd09179881bb81bea44bc165578c9f0c9bc0a033475692c8a1
- Size of remote file:
- 438 MB
- SHA256:
- ac63a315eb217837fb2f5df77dd4b44633b472ec7e4fa4b7631fe7ad2ae33fc8
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