Instructions to use AQuarterMile/WritingBench-Critic-Model-Qwen-7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use AQuarterMile/WritingBench-Critic-Model-Qwen-7B with Transformers:

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

pipe = pipeline("text-generation", model="AQuarterMile/WritingBench-Critic-Model-Qwen-7B")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("AQuarterMile/WritingBench-Critic-Model-Qwen-7B")
model = AutoModelForCausalLM.from_pretrained("AQuarterMile/WritingBench-Critic-Model-Qwen-7B")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Inference
Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use AQuarterMile/WritingBench-Critic-Model-Qwen-7B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "AQuarterMile/WritingBench-Critic-Model-Qwen-7B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "AQuarterMile/WritingBench-Critic-Model-Qwen-7B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/AQuarterMile/WritingBench-Critic-Model-Qwen-7B

SGLang

How to use AQuarterMile/WritingBench-Critic-Model-Qwen-7B 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 "AQuarterMile/WritingBench-Critic-Model-Qwen-7B" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "AQuarterMile/WritingBench-Critic-Model-Qwen-7B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

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 "AQuarterMile/WritingBench-Critic-Model-Qwen-7B" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "AQuarterMile/WritingBench-Critic-Model-Qwen-7B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use AQuarterMile/WritingBench-Critic-Model-Qwen-7B with Docker Model Runner:
```
docker model run hf.co/AQuarterMile/WritingBench-Critic-Model-Qwen-7B
```

nielsr HF Staff commited on Mar 12, 2025

Commit

a77f3b6

verified ·

1 Parent(s): 9673942

Add pipeline tag: text-generation

Browse files

This PR adds the `pipeline_tag: text-generation` to the model card metadata. This will allow the model to be more easily discoverable through the Hugging Face model search functionality.

Files changed (1) hide show

README.md +4 -1

README.md CHANGED Viewed

@@ -1,15 +1,17 @@
 ---
 library_name: transformers
 license: apache-2.0
-base_model: Qwen/Qwen2.5-7B-Instruct
 tags:
 - llama-factory
 - generated_from_trainer
 model-index:
 - name: WritingBench-Critic-Model-Qwen-7B
   results: []
 ---
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 should probably proofread and complete it, then remove this comment. -->
@@ -59,4 +61,5 @@ The following hyperparameters were used during training:
       year={2025},
       url={https://arxiv.org/abs/2503.05244},
 }
 ```

 ---
+base_model: Qwen/Qwen2.5-7B-Instruct
 library_name: transformers
 license: apache-2.0
 tags:
 - llama-factory
 - generated_from_trainer
+pipeline_tag: text-generation
 model-index:
 - name: WritingBench-Critic-Model-Qwen-7B
   results: []
 ---
+```markdown
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 should probably proofread and complete it, then remove this comment. -->
       year={2025},
       url={https://arxiv.org/abs/2503.05244},
 }
+```
 ```