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
```

Improve model card and add paper link

by nielsr HF Staff - opened Apr 28

base: refs/heads/main

←

from: refs/pr/1

Discussion Files changed

+21

-24

nielsr

Apr 28

This PR improves the model card by:

Adding a link to the research paper: C-MORAL: Controllable Multi-Objective Molecular Optimization with Reinforcement Alignment for LLMs.
Formatting the GitHub link and project information for better discoverability.
Adding a BibTeX citation section.
Ensuring metadata is correctly formatted (identifying peft as the library and text-generation as the pipeline tag).

Improve model card and add paper link7ba59918

Rwigie

Apr 28

Thanks a lot for improving the model card and adding the paper link and citation! The updates look good to me. I’m checking why the merge button is not showing on my side.

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