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---
language:
- uk
- en
license: apache-2.0
library_name: peft
tags:
- translation
- mlx
datasets:
- Helsinki-NLP/opus_paracrawl
- turuta/Multi30k-uk
metrics:
- bleu
pipeline_tag: text-generation
base_model: mistralai/Mistral-7B-v0.1
widget:
- text: '[INST] who holds this neighborhood? [/INST]'
model-index:
- name: Dragoman
results:
- task:
type: translation
name: English-Ukrainian Translation
dataset:
name: FLORES-101
type: facebook/flores
config: eng_Latn-ukr_Cyrl
split: devtest
metrics:
- type: bleu
value: 32.34
name: Test BLEU
---
# lang-uk/dragoman-4bit
This model was converted to MLX format from the [`lang-uk/dragoman`](https://huggingface.co/lang-uk/dragoman) adapter fused into the [`mistralai/Mistral-7b-v0.1`](https://huggingface.co/mistralai/Mistral-7B-v0.1)
base model and quantized into 4 bits using mlx-lm version **0.4.0**.
Refer to the [original model card](https://huggingface.co/lang-uk/dragoman) for more details on the model.
## Use with mlx
```bash
pip install mlx-lm
```
```python
from mlx_lm import load, generate
model, tokenizer = load("lang-uk/dragoman-4bit")
response = generate(model, tokenizer, prompt="hello", verbose=True)
```
Or use from your shell:
```console
python -m mlx_lm.generate --model lang-uk/dragoman-4bit --prompt '[INST] who holds this neighborhood? [/INST]' --temp 0 --max-tokens 100
```
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