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 pytorch_model.bin from Himanshusingh/finetunedfinbert-model: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/Himanshusingh/finetunedfinbert-model/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Himanshusingh/finetunedfinbert-model/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Himanshusingh/finetunedfinbert-model/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 6f8a1d450a3b50b420992804dc204c3abca42df6cb34ffe745f76cde842a80bf
- Size of remote file:
- 438 MB
- SHA256:
- 0972f97c437a6f572ada4c68d3e6cbbaf752c02aaaf3df88e6e91156fd7c45e5
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