Instructions to use SteveBabb10M/manx-mt-gv-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SteveBabb10M/manx-mt-gv-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="SteveBabb10M/manx-mt-gv-en")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("SteveBabb10M/manx-mt-gv-en") model = AutoModelForSeq2SeqLM.from_pretrained("SteveBabb10M/manx-mt-gv-en") - Notebooks
- Google Colab
- Kaggle
| pipeline_tag: translation | |
| tags: | |
| - translation | |
| - marian | |
| - manx | |
| - gaelic | |
| - en | |
| - gv | |
| library_name: transformers | |
| language: | |
| - en | |
| - gv | |
| # Manx Translation Model (Manx to English) | |
| Fine-tuned MarianMT model for Manx to English translation, trained on 107K parallel pairs. | |
| ## Usage | |
| ```python | |
| from transformers import MarianMTModel, MarianTokenizer | |
| model_name = "SteveBabb10M/manx-mt-gv-en" | |
| 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) | |
| ``` | |