mlx-community/gte-Qwen2-1.5B-instruct-4bit-dwq
This model mlx-community/gte-Qwen2-1.5B-instruct-4bit-dwq was converted to MLX format from Alibaba-NLP/gte-Qwen2-1.5B-instruct using mlx-lm version 0.24.0.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("mlx-community/gte-Qwen2-1.5B-instruct-4bit-dwq")
prompt = "hello"
if tokenizer.chat_template is not None:
messages = [{"role": "user", "content": prompt}]
prompt = tokenizer.apply_chat_template(
messages, add_generation_prompt=True
)
response = generate(model, tokenizer, prompt=prompt, verbose=True)
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Model tree for mlx-community/gte-Qwen2-1.5B-instruct-4bit-dwq
Base model
Alibaba-NLP/gte-Qwen2-1.5B-instructEvaluation results
- accuracy on MTEB AmazonCounterfactualClassification (en)test set self-reported83.985
- ap on MTEB AmazonCounterfactualClassification (en)test set self-reported50.930
- f1 on MTEB AmazonCounterfactualClassification (en)test set self-reported78.504
- accuracy on MTEB AmazonPolarityClassificationtest set self-reported96.611
- ap on MTEB AmazonPolarityClassificationtest set self-reported94.892
- f1 on MTEB AmazonPolarityClassificationtest set self-reported96.609
- accuracy on MTEB AmazonReviewsClassification (en)test set self-reported55.614
- f1 on MTEB AmazonReviewsClassification (en)test set self-reported54.906
- map_at_1 on MTEB ArguAnatest set self-reported45.164
- map_at_10 on MTEB ArguAnatest set self-reported61.519