Instructions to use tomofusa/exp020-simpo-merged with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use tomofusa/exp020-simpo-merged with Transformers:

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

pipe = pipeline("text-generation", model="tomofusa/exp020-simpo-merged")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForMultimodalLM

tokenizer = AutoTokenizer.from_pretrained("tomofusa/exp020-simpo-merged")
model = AutoModelForMultimodalLM.from_pretrained("tomofusa/exp020-simpo-merged")
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]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use tomofusa/exp020-simpo-merged with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "tomofusa/exp020-simpo-merged"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "tomofusa/exp020-simpo-merged",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/tomofusa/exp020-simpo-merged

SGLang

How to use tomofusa/exp020-simpo-merged 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 "tomofusa/exp020-simpo-merged" \
    --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": "tomofusa/exp020-simpo-merged",
		"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 "tomofusa/exp020-simpo-merged" \
        --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": "tomofusa/exp020-simpo-merged",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Unsloth Studio

How to use tomofusa/exp020-simpo-merged with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for tomofusa/exp020-simpo-merged to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for tomofusa/exp020-simpo-merged to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for tomofusa/exp020-simpo-merged to start chatting

Load model with FastModel

pip install unsloth
from unsloth import FastModel
model, tokenizer = FastModel.from_pretrained(
    model_name="tomofusa/exp020-simpo-merged",
    max_seq_length=2048,
)

Docker Model Runner
How to use tomofusa/exp020-simpo-merged with Docker Model Runner:
```
docker model run hf.co/tomofusa/exp020-simpo-merged
```

tomofusa commited on Feb 26

Commit

f6145ee

verified ·

1 Parent(s): 433d5e5

Upload README.md with huggingface_hub

Browse files

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README.md +26 -13

README.md CHANGED Viewed

@@ -1,21 +1,34 @@
 ---
-base_model: tomofusa/exp020-simpo-merged
-tags:
-- text-generation-inference
-- transformers
-- unsloth
-- qwen3
-license: apache-2.0
 language:
 - en
 ---
-# Uploaded finetuned  model
-- **Developed by:** tomofusa
-- **License:** apache-2.0
-- **Finetuned from model :** tomofusa/exp020-simpo-merged
-This qwen3 model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
-[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)

 ---
+base_model: Qwen/Qwen3-4B-Instruct-2507
+datasets:
+- u-10bei/dpo-dataset-qwen-cot
 language:
 - en
+license: apache-2.0
+library_name: transformers
+pipeline_tag: text-generation
+tags:
+- cpo
+- simpo
+- unsloth
+- qwen
+- alignment
 ---
+# exp020-simpo-merged
+SFT + CPO/SimPO merged model. Full 16-bit weights, no adapter loading required.
+## Training Pipeline
+1. **SFT**: tomofusa/exp015-blend-h-lora
+2. **CPO/SimPO**: u-10bei/dpo-dataset-qwen-cot (1 epoch, lr=5e-07, beta=2.5)
+## CPO/SimPO Configuration
+- **Trainer**: CPOTrainer (reference-free)
+- **Loss type**: simpo
+- **Learning rate**: 5e-07
+- **Beta**: 2.5 (SimPO scale, NOT DPO scale)
+- **SimPO gamma**: 1.375
+- **CPO alpha**: 0.0
+- **LoRA**: r=64, alpha=128
+- **Max length**: 1024