Instructions to use dipta007/decomposeRL-7b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use dipta007/decomposeRL-7b with Transformers:

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

pipe = pipeline("text-generation", model="dipta007/decomposeRL-7b")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("dipta007/decomposeRL-7b")
model = AutoModelForCausalLM.from_pretrained("dipta007/decomposeRL-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]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use dipta007/decomposeRL-7b with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "dipta007/decomposeRL-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": "dipta007/decomposeRL-7b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/dipta007/decomposeRL-7b

SGLang

How to use dipta007/decomposeRL-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 "dipta007/decomposeRL-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": "dipta007/decomposeRL-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 "dipta007/decomposeRL-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": "dipta007/decomposeRL-7b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use dipta007/decomposeRL-7b with Docker Model Runner:
```
docker model run hf.co/dipta007/decomposeRL-7b
```

decomposeRL-7b / README.md

Commit History

Fix Highlights accuracy to match results table (macro 86.3, micro 84.4)

ccd85b9
verified

dipta007 commited on Jun 6

Update README: real arXiv link (2605.27858) + add citation (#1)

0d0bffb

dipta007 commited on Jun 6

Update

70ca118
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dipta007 commited on May 23

Update README

df8336a
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dipta007 commited on May 23

Update README

257b03c
verified

dipta007 commited on May 23

Add in-domain baseline comparison table

910375e
verified

dipta007 commited on May 23

Trim example to 2 iterations with per-iter think blocks

663efe3
verified

dipta007 commited on May 23

Update model card: 7 rewards, OOD coverbench, pretty-print helper, fix max-len

486896f
verified

dipta007 commited on May 23

Add detailed model card

188754b
verified

dipta007 commited on May 23

Unsloth Model Card

81a8ce8
verified

dipta007 commited on May 23

Commit History

Fix Highlights accuracy to match results table (macro 86.3, micro 84.4) ccd85b9 verified

Update README: real arXiv link (2605.27858) + add citation (#1) 0d0bffb

Update 70ca118 verified

Update README df8336a verified

Update README 257b03c verified

Add in-domain baseline comparison table 910375e verified

Trim example to 2 iterations with per-iter think blocks 663efe3 verified

Update model card: 7 rewards, OOD coverbench, pretty-print helper, fix max-len 486896f verified

Add detailed model card 188754b verified

Unsloth Model Card 81a8ce8 verified

Fix Highlights accuracy to match results table (macro 86.3, micro 84.4)

ccd85b9
verified

Update README: real arXiv link (2605.27858) + add citation (#1)

0d0bffb

Update

70ca118
verified

Update README

df8336a
verified

Update README

257b03c
verified

Add in-domain baseline comparison table

910375e
verified

Trim example to 2 iterations with per-iter think blocks

663efe3
verified

Update model card: 7 rewards, OOD coverbench, pretty-print helper, fix max-len

486896f
verified

Add detailed model card

188754b
verified

Unsloth Model Card

81a8ce8
verified