Instructions to use qihoo360/360Zhinao-1.8B-Reranking with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use qihoo360/360Zhinao-1.8B-Reranking with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="qihoo360/360Zhinao-1.8B-Reranking", trust_remote_code=True)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("qihoo360/360Zhinao-1.8B-Reranking", trust_remote_code=True, dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use qihoo360/360Zhinao-1.8B-Reranking with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "qihoo360/360Zhinao-1.8B-Reranking"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "qihoo360/360Zhinao-1.8B-Reranking",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/qihoo360/360Zhinao-1.8B-Reranking

SGLang

How to use qihoo360/360Zhinao-1.8B-Reranking with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "qihoo360/360Zhinao-1.8B-Reranking" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "qihoo360/360Zhinao-1.8B-Reranking",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "qihoo360/360Zhinao-1.8B-Reranking" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "qihoo360/360Zhinao-1.8B-Reranking",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use qihoo360/360Zhinao-1.8B-Reranking with Docker Model Runner:
```
docker model run hf.co/qihoo360/360Zhinao-1.8B-Reranking
```

Update model metadata to set pipeline tag to the new `text-ranking` and tags to `sentence-transformers`

by tomaarsen HF Staff - opened Apr 2, 2025

base: refs/heads/main

←

from: refs/pr/3

Discussion Files changed

-22

tomaarsen

Apr 2, 2025

Hello!

Pull Request overview

Update metadata to set pipeline tag to the new text-ranking
Update metadata to set tags to sentence-transformers

Changes

This is an automated pull request to update the metadata of the model card. We recently introduced the text-ranking pipeline tag for models that are used for ranking tasks, and we have a suspicion that this model is one of them. I also updated added metadata to specify that this model can be loaded with the sentence-transformers library, as it should be possible to load any model compatible with transformers AutoModelForSequenceClassification.

Feel free to verify that it works with the following:

pip install sentence-transformers

from sentence_transformers import CrossEncoder

model = CrossEncoder("qihoo360/360Zhinao-1.8B-Reranking")
scores = model.predict([
    ("How many people live in Berlin?", "Berlin had a population of 3,520,031 registered inhabitants in an area of 891.82 square kilometers."),
    ("How many people live in Berlin?", "Berlin is well known for its museums."),
])
print(scores)

Feel free to respond if you have questions or concerns.

Tom Aarsen

Update model metadata to set pipeline tag to the new `text-ranking` and tags to `sentence-transformers`619f854a

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