Instructions to use deepesh0x/autotrain-mlsec-1013333726 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use deepesh0x/autotrain-mlsec-1013333726 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="deepesh0x/autotrain-mlsec-1013333726")# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForSequenceClassification model = AutoModelForSequenceClassification.from_pretrained("deepesh0x/autotrain-mlsec-1013333726", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download sample_input.pkl from deepesh0x/autotrain-mlsec-1013333726: direct link, hf CLI and curl.
- Browser
- Download file 9.21 kB
-
https://huggingface.co/deepesh0x/autotrain-mlsec-1013333726/resolve/main/sample_input.pkl
- Command line
-
hf download hf://deepesh0x/autotrain-mlsec-1013333726/sample_input.pkl
-
curl -L -o sample_input.pkl https://huggingface.co/deepesh0x/autotrain-mlsec-1013333726/resolve/main/sample_input.pkl
9.21 kB
- Xet hash:
- 44a7703cb36b434270e9d982779cf436e469a9ca905f19c396892ad662ef1a31
- Size of remote file:
- 9.21 kB
- SHA256:
- 30aa7c9c59e6b1de09c3b6e0029a400c9cf66eae1d48c3d30fd2a78c0f471313
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