Translation
Transformers
Safetensors
English
llama
text-generation
Eval Results (legacy)
text-generation-inference
Instructions to use westenfelder/Llama-3.2-3B-Instruct-NL2SH with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use westenfelder/Llama-3.2-3B-Instruct-NL2SH 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="westenfelder/Llama-3.2-3B-Instruct-NL2SH")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("westenfelder/Llama-3.2-3B-Instruct-NL2SH") model = AutoModelForCausalLM.from_pretrained("westenfelder/Llama-3.2-3B-Instruct-NL2SH", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Add model card metadata and link to code repository
#1
by nielsr HF Staff - opened
This PR improves the model card by adding the relevant pipeline_tag (text-generation), library_name, license and link to the Github repository.
westenfelder changed pull request status to merged