Instructions to use Rwigle/C-MORAL-Mistral-GRPO with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries
PEFT
How to use Rwigle/C-MORAL-Mistral-GRPO with PEFT:
```
Task type is invalid.
```

How to use Rwigle/C-MORAL-Mistral-GRPO with Transformers:

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

pipe = pipeline("text-generation", model="Rwigle/C-MORAL-Mistral-GRPO")

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("Rwigle/C-MORAL-Mistral-GRPO", dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Rwigle/C-MORAL-Mistral-GRPO with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/Rwigle/C-MORAL-Mistral-GRPO

SGLang

How to use Rwigle/C-MORAL-Mistral-GRPO 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 "Rwigle/C-MORAL-Mistral-GRPO" \
    --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": "Rwigle/C-MORAL-Mistral-GRPO",
		"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 "Rwigle/C-MORAL-Mistral-GRPO" \
        --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": "Rwigle/C-MORAL-Mistral-GRPO",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Rwigle/C-MORAL-Mistral-GRPO with Docker Model Runner:
```
docker model run hf.co/Rwigle/C-MORAL-Mistral-GRPO
```

Rwigle commited on Apr 24

Commit

5023b26

verified ·

1 Parent(s): 63632ca

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bpq/README.md +2 -1

bpq/README.md CHANGED Viewed

@@ -9,6 +9,7 @@ tags:
 - mistral
 - grpo
 - molecule-optimization
 license: mit
 ---
@@ -22,7 +23,7 @@ LoRA adapter for molecule optimization trained with GRPO on the `bpq` task.
 ## Task
-- `bpq`
 - property combination: `bbbp+plogp+qed`
 ## Method

 - mistral
 - grpo
 - molecule-optimization
+- bpq
 license: mit
 ---
 ## Task
+- task alias: `bpq`
 - property combination: `bbbp+plogp+qed`
 ## Method