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t5
text2text-generation
seq2seq
text-generation-inference
Instructions to use yhavinga/t5-base-36L-ccmatrix-multi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yhavinga/t5-base-36L-ccmatrix-multi 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="yhavinga/t5-base-36L-ccmatrix-multi")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("yhavinga/t5-base-36L-ccmatrix-multi") model = AutoModelForSeq2SeqLM.from_pretrained("yhavinga/t5-base-36L-ccmatrix-multi", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "test_bp": 0.9413807776309435, | |
| "test_precision_ng1": 76.01892285298399, | |
| "test_precision_ng2": 54.01958080529509, | |
| "test_precision_ng3": 41.72523961661342, | |
| "test_precision_ng4": 32.91607396870555, | |
| "test_ref_len": 17484, | |
| "test_score": 45.87597143301609, | |
| "test_sys_len": 16488 | |
| } |