Instructions to use Ammok/predict-llm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ammok/predict-llm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Ammok/predict-llm")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Ammok/predict-llm") model = AutoModelForSequenceClassification.from_pretrained("Ammok/predict-llm", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Ammok/predict-llm: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/Ammok/predict-llm/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Ammok/predict-llm/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Ammok/predict-llm/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 4e283e6278a816ceeba87d769600be10f523388918da56f6cefa711d34e349df
- Size of remote file:
- 438 MB
- SHA256:
- 0ea4dd53bf00d458afcab1adabccdf3d2ba5ba81ff7627cbfca9498668893bbf
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