Text Generation
Transformers
Safetensors
gemma2
mergekit
Merge
conversational
text-generation-inference
Instructions to use TheDrummer/Gemmasutra-9B-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TheDrummer/Gemmasutra-9B-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="TheDrummer/Gemmasutra-9B-v1") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("TheDrummer/Gemmasutra-9B-v1") model = AutoModelForCausalLM.from_pretrained("TheDrummer/Gemmasutra-9B-v1", device_map="auto") 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 TheDrummer/Gemmasutra-9B-v1 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "TheDrummer/Gemmasutra-9B-v1" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "TheDrummer/Gemmasutra-9B-v1", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/TheDrummer/Gemmasutra-9B-v1
- SGLang
How to use TheDrummer/Gemmasutra-9B-v1 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 "TheDrummer/Gemmasutra-9B-v1" \ --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": "TheDrummer/Gemmasutra-9B-v1", "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 "TheDrummer/Gemmasutra-9B-v1" \ --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": "TheDrummer/Gemmasutra-9B-v1", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use TheDrummer/Gemmasutra-9B-v1 with Docker Model Runner:
docker model run hf.co/TheDrummer/Gemmasutra-9B-v1
metadata
base_model:
- BeaverAI/Gemmasutra-9B-v1b
- BeaverAI/Gemmasutra-9B-v1a
library_name: transformers
tags:
- mergekit
- merge
Join our Discord! https://discord.gg/Nbv9pQ88Xb
BeaverAI team proudly presents
Gemmasutra 9B v1 🧘
Gemma's been training for you
An RP model with impressive flexibility. Finetuned by yours truly.
Links
- Original: https://huggingface.co/TheDrummer/Gemmasutra-9B-v1
- GGUF: https://huggingface.co/TheDrummer/Gemmasutra-9B-v1-GGUF
- Extremely Moist but Maybe Stupid Test Model: https://huggingface.co/BeaverAI/Gemmasutra-9B-v1b-GGUF
Usage
Use Kobold: https://github.com/LostRuins/koboldcpp/releases
What's Different?
- Engaging Roleplay
- Asterisks-capable
- Long responses
- Barely any mention of (You)
- Creative!
- Enhanced Moist
- Less slop, more dirt, more details, more dwelling on moist moments.
- Important: This is an RP-enhanced model with some degree of censorship.
- WHY: Refusals allow the AI to roleplay certain behaviors like avoidance, rejection, etc.
- Use Tiger Gemma if you want zero refusals as an Assistant / during Instruct mode.
v1c


