Instructions to use Parth/result with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Parth/result with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Parth/result") model = AutoModelForSeq2SeqLM.from_pretrained("Parth/result", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from Parth/result: direct link, hf CLI and curl.
- Browser
- Download file 892 MB
-
https://huggingface.co/Parth/result/resolve/refs%2Fpr%2F1/flax_model.msgpack
- Command line
-
hf download hf://Parth/result@refs/pr/1/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/Parth/result/resolve/refs%2Fpr%2F1/flax_model.msgpack
892 MB
- Xet hash:
- d96777681381d2444d5dac6f27fdd0ae396f2a16110bb2dd3f35fe74c17ab351
- Size of remote file:
- 892 MB
- SHA256:
- 1906f6b6b41169df931068688a6c87ae7b3ab34ba740d91b2ddb404cd13304af
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