Instructions to use Data-Lab/marat_model_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Data-Lab/marat_model_test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Data-Lab/marat_model_test")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Data-Lab/marat_model_test") model = AutoModelForSequenceClassification.from_pretrained("Data-Lab/marat_model_test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Data-Lab/marat_model_test: direct link, hf CLI and curl.
- Browser
- Download file 514 MB
-
https://huggingface.co/Data-Lab/marat_model_test/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://Data-Lab/marat_model_test@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Data-Lab/marat_model_test/resolve/refs%2Fpr%2F1/pytorch_model.bin
514 MB
- Xet hash:
- fbb4884acc8a40d536ad097518dc903cda70ddaf124f8f221e1494626e4de872
- Size of remote file:
- 514 MB
- SHA256:
- a822f232f1a1dc701d896045c96a0674433802dcfd746b509eaffc104adb5f33
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