Instructions to use TIGER-Lab/AceCodeRM-32B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TIGER-Lab/AceCodeRM-32B with Transformers:
# Load model directly from transformers import AutoTokenizer, Qwen2ForCausalRM tokenizer = AutoTokenizer.from_pretrained("TIGER-Lab/AceCodeRM-32B") model = Qwen2ForCausalRM.from_pretrained("TIGER-Lab/AceCodeRM-32B") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5bb2f7e55f40de622337431b2866f1ea5221462063498aea4943c8bd4c26dd25
- Size of remote file:
- 11.4 MB
- SHA256:
- ba0c439f7be467bf47d12a7e6f9adc6116201056fc60c67f431c679b7c16afc8
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