Instructions to use NiuTrans/LMT-60-8B-Base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NiuTrans/LMT-60-8B-Base 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="NiuTrans/LMT-60-8B-Base")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("NiuTrans/LMT-60-8B-Base") model = AutoModelForCausalLM.from_pretrained("NiuTrans/LMT-60-8B-Base") - Notebooks
- Google Colab
- Kaggle
Improve model card: Add `library_name`, update `pipeline_tag`, and correct `language` entry
#2
by nielsr HF Staff - opened
This PR enhances the model card by:
- Adding
library_name: transformersto the metadata, which enables the interactive "how to use" widget on the Hugging Face Hub, making it easier for users to get started with the model. This is supported by thetransformerslibrary usage in the "Quickstart" section. - Updating the
pipeline_tagfromtranslationtotext-generationas per guidelines for generative language models, and addingtranslationas an additionaltagfor better categorization. - Correcting the invalid
language: falseentry tolanguage: no(Norwegian), ensuring the language list accurately reflects the 60 languages supported by the model as detailed in the "Support Languages" section.