Instructions to use Souvik123/results with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Souvik123/results with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("question-answering", model="Souvik123/results")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("Souvik123/results") model = AutoModelForQuestionAnswering.from_pretrained("Souvik123/results", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Souvik123/results: direct link, hf CLI and curl.
- Browser
- Download file 265 MB
-
https://huggingface.co/Souvik123/results/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Souvik123/results/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Souvik123/results/resolve/main/pytorch_model.bin
265 MB
- Xet hash:
- 5ab73d2cc0270f57d11083380bac68a0a12d769f55dcadf7d9f0767de20a6807
- Size of remote file:
- 265 MB
- SHA256:
- 612672cae8c814ab6e049b212f5101f8d4c0485471d2af15c4f2d547b79c6c77
路
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