Instructions to use Novaciano/Proto_RP-Gemma2-2B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Novaciano/Proto_RP-Gemma2-2B with Transformers:

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

pipe = pipeline("text-generation", model="Novaciano/Proto_RP-Gemma2-2B")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Novaciano/Proto_RP-Gemma2-2B")
model = AutoModelForCausalLM.from_pretrained("Novaciano/Proto_RP-Gemma2-2B")
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

vLLM

How to use Novaciano/Proto_RP-Gemma2-2B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Novaciano/Proto_RP-Gemma2-2B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Novaciano/Proto_RP-Gemma2-2B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Novaciano/Proto_RP-Gemma2-2B

SGLang

How to use Novaciano/Proto_RP-Gemma2-2B 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 "Novaciano/Proto_RP-Gemma2-2B" \
    --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": "Novaciano/Proto_RP-Gemma2-2B",
		"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 "Novaciano/Proto_RP-Gemma2-2B" \
        --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": "Novaciano/Proto_RP-Gemma2-2B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use Novaciano/Proto_RP-Gemma2-2B with Docker Model Runner:
```
docker model run hf.co/Novaciano/Proto_RP-Gemma2-2B
```
Browse Quantizations to use this model in llama.cpp, Ollama, LM Studio, or any compatible app.

Proto_RP-Gemma2-2B

This garbage still has heavy censorship; I still need to figure out how to remove it. Maybe I can manage it with future remixes.

The prototype is ideal for creating stories with dialogue, but... it's still not suitable for creating sexual stories.

Merge Method

This model was merged using the Model Stock merge method using TheDrummer/Gemmasutra-Mini-2B-v1 as a base.

Models Merged

The following models were included in the merge:

Configuration

The following YAML configuration was used to produce this model:

merge_method: model_stock
dtype: bfloat16
out_dtype: bfloat16

# Base model: provides narrative richness, sensory detail, and RP flow
base_model: TheDrummer/Gemmasutra-Mini-2B-v1

parameters:
  t:
    - 0.95  # ChiKoi7/Gemma-2-Llama-Swallow-2b-it-v0.1-Heretic
            # Dominant driver: heretic alignment, reduced refusals, breaks moral consensus
    - 0.55  # ArliAI/Gemma-2-2B-ArliAI-RPMax-v1.1
            # Structural RP reinforcement: dialogue consistency, character stability
    - 0.35  # akashgoel-id/En_RP_DPO-gemma2_2b_64X32_test
            # Light DPO stabilization: conversational smoothness without enforcing censorship

models:
  - model: ChiKoi7/Gemma-2-Llama-Swallow-2b-it-v0.1-Heretic
  - model: ArliAI/Gemma-2-2B-ArliAI-RPMax-v1.1
  - model: akashgoel-id/En_RP_DPO-gemma2_2b_64X32_test