Instructions to use zstanjj/SlimPLM-Retrieval-Necessity-Judgment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use zstanjj/SlimPLM-Retrieval-Necessity-Judgment with Transformers:

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

pipe = pipeline("text-generation", model="zstanjj/SlimPLM-Retrieval-Necessity-Judgment")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("zstanjj/SlimPLM-Retrieval-Necessity-Judgment")
model = AutoModelForCausalLM.from_pretrained("zstanjj/SlimPLM-Retrieval-Necessity-Judgment")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use zstanjj/SlimPLM-Retrieval-Necessity-Judgment with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/zstanjj/SlimPLM-Retrieval-Necessity-Judgment

SGLang

How to use zstanjj/SlimPLM-Retrieval-Necessity-Judgment 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 "zstanjj/SlimPLM-Retrieval-Necessity-Judgment" \
    --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": "zstanjj/SlimPLM-Retrieval-Necessity-Judgment",
		"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 "zstanjj/SlimPLM-Retrieval-Necessity-Judgment" \
        --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": "zstanjj/SlimPLM-Retrieval-Necessity-Judgment",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use zstanjj/SlimPLM-Retrieval-Necessity-Judgment with Docker Model Runner:
```
docker model run hf.co/zstanjj/SlimPLM-Retrieval-Necessity-Judgment
```

zstanjj commited on Oct 16, 2024

Commit

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@@ -23,7 +23,7 @@ license: llama2
 - [1/25/2024]: Retrieval Necessity Judgment Model released in [Hugging Face](https://huggingface.co/zstanjj/SlimPLM-Retrieval-Necessity-Judgment/).
 - [2/20/2024]: Query Rewriting Model released in [Hugging Face](https://huggingface.co/zstanjj/SlimPLM-Query-Rewriting/).
-- [5/19/2024]: Our new work, **[SlimPLM](https://github.com/plageon/SlimPlm)**, has been accepted by **ACL 2024 main** conference.
 ## 🎬 Get Started

 - [1/25/2024]: Retrieval Necessity Judgment Model released in [Hugging Face](https://huggingface.co/zstanjj/SlimPLM-Retrieval-Necessity-Judgment/).
 - [2/20/2024]: Query Rewriting Model released in [Hugging Face](https://huggingface.co/zstanjj/SlimPLM-Query-Rewriting/).
+- [5/19/2024]: Our new work, **[Small Models, Big Insights: Leveraging Slim Proxy Models To Decide When and What to Retrieve for LLMs](https://aclanthology.org/2024.acl-long.242/)**, has been accepted by **ACL 2024 main** conference.
 ## 🎬 Get Started