Translation
Transformers
PyTorch
TensorBoard
Safetensors
English
marian
text2text-generation
Generated from Trainer
Instructions to use SRDdev/HingFlow with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SRDdev/HingFlow with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "translation" 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("translation", model="SRDdev/HingFlow")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("SRDdev/HingFlow") model = AutoModelForSeq2SeqLM.from_pretrained("SRDdev/HingFlow", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from SRDdev/HingFlow: direct link, hf CLI and curl.
- Browser
- Download file 304 MB
-
https://huggingface.co/SRDdev/HingFlow/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://SRDdev/HingFlow/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/SRDdev/HingFlow/resolve/main/pytorch_model.bin
304 MB
- Xet hash:
- 37c4384fb4f2ea782aa4139d2606fe03f59441324deb8ecf1320b9abd1822958
- Size of remote file:
- 304 MB
- SHA256:
- 5e323d01aaf1838bf2030fb7ccabcf50843d1a15b02f744f6e8b27dab188f44d
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