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nisavid/mxbai-rerank-large-v2-mlx-4bit
mxbai-rerank-large-v2-mlx-4bit is a text ranking model from nisavid. Use it for the text ranking task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as apache-2.0.
The Model nisavid/mxbai-rerank-large-v2-mlx-4Bit was converted to MLX format from mixedbread-ai/mxbai-rerank-large-v2 using mlx-lm version 0.31.2.
Downloads · 30 days
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.safetensors869 MB · 99%
How the weights are stored.
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From the Hugging Face model README
The Model nisavid/mxbai-rerank-large-v2-mlx-4Bit was converted to MLX format from mixedbread-ai/mxbai-rerank-large-v2 using mlx-lm version 0.31.2.
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("nisavid/mxbai-rerank-large-v2-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)