metadata

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 for more details on the model.

Use with mlx

pip install mlx-lm

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)