Instructions to use SteveBabb10M/manx-mt-en-gv with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SteveBabb10M/manx-mt-en-gv 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="SteveBabb10M/manx-mt-en-gv")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("SteveBabb10M/manx-mt-en-gv") model = AutoModelForSeq2SeqLM.from_pretrained("SteveBabb10M/manx-mt-en-gv") - Notebooks
- Google Colab
- Kaggle
Manx Translation Model (English to Manx)
Fine-tuned MarianMT model for English to Manx translation, trained on 107K parallel pairs.
Usage
from transformers import MarianMTModel, MarianTokenizer
model_name = "SteveBabb10M/manx-mt-en-gv"
tokenizer = MarianTokenizer.from_pretrained(model_name)
model = MarianMTModel.from_pretrained(model_name)
text = "The parliament was very old."
inputs = tokenizer(text, return_tensors="pt", padding=True)
translated = model.generate(**inputs)
result = tokenizer.decode(translated[0], skip_special_tokens=True)
print(result)
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