Instructions to use mrfriedpotato/perform with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mrfriedpotato/perform with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mrfriedpotato/perform")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mrfriedpotato/perform") model = AutoModelForSequenceClassification.from_pretrained("mrfriedpotato/perform", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from mrfriedpotato/perform: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/mrfriedpotato/perform/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://mrfriedpotato/perform/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/mrfriedpotato/perform/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 16e18e5014d620cd674a116e6ae7f09d4fce1ffb3228fbd7a18558c430bdc3a1
- Size of remote file:
- 438 MB
- SHA256:
- a2644c0f7b4af9c01c2223db10cf003168383b543796f7e109bdc41f80e33800
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