Instructions to use Rahul-G/MAL-10epoch-MLMMul with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Rahul-G/MAL-10epoch-MLMMul with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Rahul-G/MAL-10epoch-MLMMul")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Rahul-G/MAL-10epoch-MLMMul") model = AutoModelForSequenceClassification.from_pretrained("Rahul-G/MAL-10epoch-MLMMul", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Rahul-G/MAL-10epoch-MLMMul: direct link, hf CLI and curl.
- Browser
- Download file 2.29 GB
-
https://huggingface.co/Rahul-G/MAL-10epoch-MLMMul/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Rahul-G/MAL-10epoch-MLMMul/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Rahul-G/MAL-10epoch-MLMMul/resolve/main/pytorch_model.bin
2.29 GB
- Xet hash:
- b50b12f545861e84f5b34d4a4a6896e0b03e61806a9064e3180f49d08c87896e
- Size of remote file:
- 2.29 GB
- SHA256:
- 9ca25d917ddd46a1fc1eedab6b7a7f03df5ccb50a5b5fd701f710a8adf0f76af
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