Translation
Transformers
TensorBoard
Safetensors
marian
text2text-generation
Generated from Trainer
Eval Results (legacy)
Instructions to use sauc-abadal-lloret/opus-mt-ca-en-ft-kde4-mt-ca-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sauc-abadal-lloret/opus-mt-ca-en-ft-kde4-mt-ca-en 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="sauc-abadal-lloret/opus-mt-ca-en-ft-kde4-mt-ca-en")# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("sauc-abadal-lloret/opus-mt-ca-en-ft-kde4-mt-ca-en") model = AutoModelForMultimodalLM.from_pretrained("sauc-abadal-lloret/opus-mt-ca-en-ft-kde4-mt-ca-en") - Notebooks
- Google Colab
- Kaggle
opus-mt-ca-en-ft-kde4-mt-ca-en / runs /Sep09_10-58-37_5ea48e9ab359 /events.out.tfevents.1725884229.5ea48e9ab359.761.1
- Xet hash:
- 2c80f1782890f0d1e9a0d8dc9c33765e55c8af2d77da4662a1efd966ec8dc15e
- Size of remote file:
- 473 Bytes
- SHA256:
- 83fb8b97746c7d7e2113ba3308cb4eeee761600a7fe63c850e08d317b2dafca3
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