Instructions to use Himanshusingh/finetunedfinbert-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Himanshusingh/finetunedfinbert-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Himanshusingh/finetunedfinbert-model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Himanshusingh/finetunedfinbert-model") model = AutoModelForSequenceClassification.from_pretrained("Himanshusingh/finetunedfinbert-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Himanshusingh/finetunedfinbert-model: direct link, hf CLI and curl.
- Browser
- Download file 3.96 kB
-
https://huggingface.co/Himanshusingh/finetunedfinbert-model/resolve/main/training_args.bin
- Command line
-
hf download hf://Himanshusingh/finetunedfinbert-model/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Himanshusingh/finetunedfinbert-model/resolve/main/training_args.bin
3.96 kB
- Xet hash:
- 2e229b9b1fa1fbcf0f21030caccb2a8642806eb7bf63e455af3a4da7c78bf854
- Size of remote file:
- 3.96 kB
- SHA256:
- 2aa2193036e7f6af56161d852df68a0deba8a01dc2b05d57793bc5be0173d1c5
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