Instructions to use MachineLearningLawyer/moderate-101-rejection-examiner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MachineLearningLawyer/moderate-101-rejection-examiner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="MachineLearningLawyer/moderate-101-rejection-examiner")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MachineLearningLawyer/moderate-101-rejection-examiner") model = AutoModelForSequenceClassification.from_pretrained("MachineLearningLawyer/moderate-101-rejection-examiner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from MachineLearningLawyer/moderate-101-rejection-examiner: direct link, hf CLI and curl.
- Browser
- Download file 557 MB
-
https://huggingface.co/MachineLearningLawyer/moderate-101-rejection-examiner/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://MachineLearningLawyer/moderate-101-rejection-examiner/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/MachineLearningLawyer/moderate-101-rejection-examiner/resolve/main/pytorch_model.bin
557 MB
- Xet hash:
- 948f67dd746e75ee5c0ba40d3aa6476e4fe6a16e36e7eca6e936339574e304ff
- Size of remote file:
- 557 MB
- SHA256:
- ea7d725cc591d6ec59700e353241b6ac01770411efa1ba14d97721b44abfa910
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