Translation
Transformers
Safetensors
llama
text-generation
multilingual
machine-translation
reinforcement-learning
text-generation-inference
Instructions to use lyf07/LLaMAX3-8B-Alpaca-WALAR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lyf07/LLaMAX3-8B-Alpaca-WALAR 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="lyf07/LLaMAX3-8B-Alpaca-WALAR")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("lyf07/LLaMAX3-8B-Alpaca-WALAR") model = AutoModelForCausalLM.from_pretrained("lyf07/LLaMAX3-8B-Alpaca-WALAR", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Add library_name and pipeline_tag metadata
#1
by nielsr HF Staff - opened
Hi! I'm Niels, part of the community science team at Hugging Face.
I noticed that this model card is missing some metadata that would help users discover and use your model. This PR adds the library_name: transformers and pipeline_tag: translation to the YAML header. These additions will enable the inference widget on the model page and categorize the model correctly in the Hub's task filtering.
Best,
Niels
Thank you so much for your help! Really appreciate your time and effort for it!
lyf07 changed pull request status to merged