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")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("SRDdev/HingFlow") model = AutoModelForSeq2SeqLM.from_pretrained("SRDdev/HingFlow") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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metrics:
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model-index:
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results: []
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datasets:
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pipeline_tag: translation
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#
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It achieves the following results on the evaluation set:
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- Loss: 0.1887
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- Bleu: 72.3468
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metrics:
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- bleu
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model-index:
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- name: HingFlow
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results: []
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datasets:
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- cfilt/iitb-english-hindi
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pipeline_tag: translation
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# HingFlow
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It achieves the following results on the evaluation set:
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- Loss: 0.1887
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- Bleu: 72.3468
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