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:
- 0dbb04daff2b39d7f0caafd7691ef6eb6321eebbb932f9e15ae5c095010061ef
- Size of remote file:
- 5 GB
- SHA256:
- bf3b6f1ad848ad279f195ad46d7e4640f090f5a4b7ce8ec020129ad85c334761
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