Instructions to use internlm/OREAL-32B-SFT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use internlm/OREAL-32B-SFT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="internlm/OREAL-32B-SFT")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("internlm/OREAL-32B-SFT") model = AutoModelForCausalLM.from_pretrained("internlm/OREAL-32B-SFT") - Notebooks
- Google Colab
- Kaggle
Add library name, pipeline tag, and improve usage
#1
by nielsr HF Staff - opened
This PR adds the library_name (Transformers) and pipeline_tag (question-answering) to the model card, which is important metadata to ensure proper discoverability. Also, the full system prompt has been added to the model card.
RangiLyu changed pull request status to merged