Instructions to use mlx-community/TowerInstruct-v0.1-bfloat16-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-community/TowerInstruct-v0.1-bfloat16-mlx with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download mlx-community/TowerInstruct-v0.1-bfloat16-mlx --local-dir TowerInstruct-v0.1-bfloat16-mlx
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
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Download README.md from mlx-community/TowerInstruct-v0.1-bfloat16-mlx: direct link, hf CLI and curl.
- Browser
- Download file 1.66 kB
-
https://huggingface.co/mlx-community/TowerInstruct-v0.1-bfloat16-mlx/resolve/main/README.md
- Command line
-
hf download hf://mlx-community/TowerInstruct-v0.1-bfloat16-mlx/README.md
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curl -L -o README.md https://huggingface.co/mlx-community/TowerInstruct-v0.1-bfloat16-mlx/resolve/main/README.md
1.66 kB
metadata
language:
- en
- de
- fr
- zh
- pt
- nl
- ru
- ko
- it
- es
license: cc-by-nc-4.0
tags:
- mlx
metrics:
- comet
pipeline_tag: translation
mlx-community/TowerInstruct-v0.1-bfloat16-mlx
This model was converted to MLX format from Unbabel/TowerInstruct-v0.1.
Refer to the original model card for more details on the model.
Intended uses & limitations (from the original model card)
The model was initially fine-tuned on a filtered and preprocessed supervised fine-tuning dataset (TowerBlocks), which contains a diverse range of data sources:
- Translation (sentence and paragraph-level)
- Automatic Post Edition
- Machine Translation Evaluation
- Context-aware Translation
- Terminology-aware Translation
- Multi-reference Translation
- Named-entity Recognition
- Paraphrase Generation
- Synthetic Chat data
- Code instructions
You can find the dataset and all data sources of TowerBlocks here.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("mlx-community/TowerInstruct-v0.1-bfloat16-mlx")
prompt="Translate the following text from Portuguese into French.\nPortuguese: Um grupo de investigadores lançou um novo modelo para tarefas relacionadas com tradução.\nFrench:"
response = generate(model, tokenizer, prompt=prompt, verbose=True)
# Un groupe d'investigateurs a lancé un nouveau modèle pour les tâches liées à la traduction.