Instructions to use zerodegress/Index-Translate-2B-MLX-6bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use zerodegress/Index-Translate-2B-MLX-6bit with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir Index-Translate-2B-MLX-6bit zerodegress/Index-Translate-2B-MLX-6bit
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
Index-Translate-2B-MLX-6bit
MLX affine 6-bit quantization (group size 64) of IndexTeam/Index-Translate-2B. Weights only re-encoded — no retraining, no fine-tuning.
Text translation only: the upstream checkpoint's vision tower and MTP head are not included. Runs with mlx-lm on Apple Silicon; not a llama.cpp / GGUF model.
Usage
from mlx_lm import load, generate
model, tokenizer = load("zerodegress/Index-Translate-2B-MLX-6bit")
prompt = "请将以下中文文本翻译为英语,直接输出翻译结果,不要进行任何解释。\n\n你好,世界!"
print(generate(model, tokenizer, prompt=prompt, max_tokens=1024))
Prompt template: 请将以下{源语言}文本翻译为{目标语言},直接输出翻译结果,不要进行任何解释。
(the source-language slot is left empty for auto-detection). Greedy decoding, thinking disabled.
Files
| file | bytes | sha256 |
|---|---|---|
model.safetensors |
1,529,723,711 | 4431bc2e38d4b9659ff0cec043eea894b737d924f9f823dc3ea60adf55583d02 |
Plus config.json, tokenizer.json, tokenizer_config.json, vocab.json, merges.txt,
generation_config.json (copied from upstream), and MANIFEST.json (conversion record).
Attribution
Weights: IndexTeam/Index-Translate-2B (apache-2.0) · family repo. This release only re-encodes the upstream weights; no new rights are claimed.
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6-bit
Model tree for zerodegress/Index-Translate-2B-MLX-6bit
Base model
IndexTeam/Index-Translate-2B