Instructions to use CLAck/en-km with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CLAck/en-km 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="CLAck/en-km")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("CLAck/en-km") model = AutoModelForSeq2SeqLM.from_pretrained("CLAck/en-km", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- da6160b52eb8e67fe3d5a109dc537e424ff90228db33c101e499a364c987e7e2
- Size of remote file:
- 318 MB
- SHA256:
- b3f54fbef842bbd21806a34bb84f05ba6a5d8d1e44f88e352de9cbf2c537cb62
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