Instructions to use Horkios/Qwen3-Reranker-8B-mlx-4Bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Horkios/Qwen3-Reranker-8B-mlx-4Bit with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Horkios/Qwen3-Reranker-8B-mlx-4Bit") model = AutoModelForCausalLM.from_pretrained("Horkios/Qwen3-Reranker-8B-mlx-4Bit", device_map="auto") - MLX
How to use Horkios/Qwen3-Reranker-8B-mlx-4Bit with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download Horkios/Qwen3-Reranker-8B-mlx-4Bit --local-dir Qwen3-Reranker-8B-mlx-4Bit
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
Quick Links
Horkios/Qwen3-Reranker-8B-mlx-4Bit
The Model Horkios/Qwen3-Reranker-8B-mlx-4Bit was converted to MLX format from Qwen/Qwen3-Reranker-8B using mlx-lm version 0.26.4.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("Horkios/Qwen3-Reranker-8B-mlx-4Bit")
prompt="hello"
if hasattr(tokenizer, "apply_chat_template") and tokenizer.chat_template is not None:
messages = [{"role": "user", "content": prompt}]
prompt = tokenizer.apply_chat_template(
messages, tokenize=False, add_generation_prompt=True
)
response = generate(model, tokenizer, prompt=prompt, verbose=True)
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Model size
8B params
Tensor type
U32
ยท
BF16 ยท
Hardware compatibility
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4-bit
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Horkios/Qwen3-Reranker-8B-mlx-4Bit") model = AutoModelForCausalLM.from_pretrained("Horkios/Qwen3-Reranker-8B-mlx-4Bit", device_map="auto")