Instructions to use huihui-ai/Huihui-Hunyuan-MT-Chimera-7B-abliterated with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use huihui-ai/Huihui-Hunyuan-MT-Chimera-7B-abliterated 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="huihui-ai/Huihui-Hunyuan-MT-Chimera-7B-abliterated")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("huihui-ai/Huihui-Hunyuan-MT-Chimera-7B-abliterated") model = AutoModelForCausalLM.from_pretrained("huihui-ai/Huihui-Hunyuan-MT-Chimera-7B-abliterated", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d5cc239d0a437cbe40cfd014f87f33caf15034c97177842545d960b1f9c7b052
- Size of remote file:
- 4.92 GB
- SHA256:
- d3b1ed006ad8798ca907edcd7b0bd47e7f2b49f72e03e20a303f4105598b2f0f
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