| language: | |
| - en | |
| license: apache-2.0 | |
| library_name: transformers | |
| tags: | |
| - gpt | |
| - llm | |
| - large language model | |
| - h2o-llmstudio | |
| - mlx | |
| datasets: | |
| - HuggingFaceH4/ultrafeedback_binarized | |
| - Intel/orca_dpo_pairs | |
| - argilla/distilabel-math-preference-dpo | |
| - Open-Orca/OpenOrca | |
| - OpenAssistant/oasst2 | |
| - HuggingFaceH4/ultrachat_200k | |
| - meta-math/MetaMathQA | |
| thumbnail: https://h2o.ai/etc.clientlibs/h2o/clientlibs/clientlib-site/resources/images/favicon.ico | |
| widget: | |
| - text: <|prompt|>Why is drinking water so healthy?</s><|answer|> | |
| # mlx-community/h2o-danube-1.8b-chat-4bit-mlx | |
| This model was converted to MLX format from [`h2oai/h2o-danube-1.8b-chat`](). | |
| Refer to the [original model card](https://huggingface.co/h2oai/h2o-danube-1.8b-chat) for more details on the model. | |
| ## Use with mlx | |
| ```bash | |
| pip install mlx-lm | |
| ``` | |
| ```python | |
| from mlx_lm import load, generate | |
| model, tokenizer = load("mlx-community/h2o-danube-1.8b-chat-4bit-mlx") | |
| response = generate(model, tokenizer, prompt="hello", verbose=True) | |
| ``` | |