Instructions to use drkumaranu165/model_output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use drkumaranu165/model_output with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="drkumaranu165/model_output")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("drkumaranu165/model_output") model = AutoModelForTokenClassification.from_pretrained("drkumaranu165/model_output", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from drkumaranu165/model_output: direct link, hf CLI and curl.
- Browser
- Download file 5.37 kB
-
https://huggingface.co/drkumaranu165/model_output/resolve/main/training_args.bin
- Command line
-
hf download hf://drkumaranu165/model_output/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/drkumaranu165/model_output/resolve/main/training_args.bin
5.37 kB
- Xet hash:
- bcf65f84a9ec2aa181450a0bd9b66e50ecac3b888aaf592086b62fc780280509
- Size of remote file:
- 5.37 kB
- SHA256:
- 7125e14da78ecc5580f267a2d95b703fda2d058982284b3986b587cc8c1861fa
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