Instructions to use CooperBench/cooperator-qwen35-35b-a3b-sft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use CooperBench/cooperator-qwen35-35b-a3b-sft with Transformers:

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

pipe = pipeline("text-generation", model="CooperBench/cooperator-qwen35-35b-a3b-sft")
messages = [
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
            {"type": "text", "text": "What animal is on the candy?"}
        ]
    },
]
pipe(text=messages)

# Load model directly
from transformers import AutoProcessor, AutoModelForMultimodalLM

processor = AutoProcessor.from_pretrained("CooperBench/cooperator-qwen35-35b-a3b-sft")
model = AutoModelForMultimodalLM.from_pretrained("CooperBench/cooperator-qwen35-35b-a3b-sft")
messages = [
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
            {"type": "text", "text": "What animal is on the candy?"}
        ]
    },
]
inputs = processor.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(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use CooperBench/cooperator-qwen35-35b-a3b-sft with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "CooperBench/cooperator-qwen35-35b-a3b-sft"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "CooperBench/cooperator-qwen35-35b-a3b-sft",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/CooperBench/cooperator-qwen35-35b-a3b-sft

SGLang

How to use CooperBench/cooperator-qwen35-35b-a3b-sft 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 "CooperBench/cooperator-qwen35-35b-a3b-sft" \
    --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": "CooperBench/cooperator-qwen35-35b-a3b-sft",
		"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 "CooperBench/cooperator-qwen35-35b-a3b-sft" \
        --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": "CooperBench/cooperator-qwen35-35b-a3b-sft",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use CooperBench/cooperator-qwen35-35b-a3b-sft with Docker Model Runner:
```
docker model run hf.co/CooperBench/cooperator-qwen35-35b-a3b-sft
```

cooperator-qwen35-35b-a3b-sft / README.md

arpandeepk

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7b79b47 verified 2 months ago

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metadata

base_model: Qwen/Qwen3.5-35B-A3B
datasets:
  - CodeConflict/cooperator-sft-data
language:
  - en
library_name: transformers
license: apache-2.0
pipeline_tag: text-generation
tags:
  - tinker
  - tinker-cookbook
  - sft
  - cooperator
  - multi-agent
  - code
  - qwen3.5

CodeConflict/cooperator-qwen35-35b-a3b-sft

This model was fine-tuned from Qwen/Qwen3.5-35B-A3B using Tinker and tinker-cookbook.

Model details

Base model: Qwen/Qwen3.5-35B-A3B
Format: Merged model

Usage

from transformers import AutoModelForCausalLM

model = AutoModelForCausalLM.from_pretrained("CodeConflict/cooperator-qwen35-35b-a3b-sft")

Framework versions

tinker-cookbook: 0.3.0
transformers: 5.3.0
torch: 2.11.0