Text Generation
Transformers
Safetensors
English
gemma2
creative
creative writing
fiction writing
plot generation
sub-plot generation
story generation
scene continue
storytelling
fiction story
science fiction
romance
all genres
story
writing
vivid prosing
vivid writing
fiction
roleplaying
float32
swearing
rp
horror
gemma
karcher
Merge
mergekit
conversational
text-generation-inference
Instructions to use Naphula/Psychosis-9B-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Naphula/Psychosis-9B-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Naphula/Psychosis-9B-v1") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Naphula/Psychosis-9B-v1") model = AutoModelForCausalLM.from_pretrained("Naphula/Psychosis-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]:])) - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Naphula/Psychosis-9B-v1 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Naphula/Psychosis-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": "Naphula/Psychosis-9B-v1", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/Naphula/Psychosis-9B-v1
- SGLang
How to use Naphula/Psychosis-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 "Naphula/Psychosis-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": "Naphula/Psychosis-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 "Naphula/Psychosis-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": "Naphula/Psychosis-9B-v1", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use Naphula/Psychosis-9B-v1 with Docker Model Runner:
docker model run hf.co/Naphula/Psychosis-9B-v1
Create README.md
Browse files
README.md
ADDED
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---
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license: gemma
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base_model:
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- DavidAU/Gemma-The-Writer-9B
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- sam-paech/Darkest-muse-v1
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- sam-paech/Delirium-v1
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language:
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- en
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library_name: transformers
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tags:
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- creative
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- creative writing
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- fiction writing
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- plot generation
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- sub-plot generation
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- fiction writing
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- story generation
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- scene continue
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- storytelling
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- fiction story
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- science fiction
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- romance
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- all genres
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- story
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- writing
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- vivid prosing
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- vivid writing
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- fiction
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- roleplaying
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- float32
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- swearing
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- gemma2
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- rp
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- horror
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- gemma
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- karcher
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- merge
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- mergekit
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widget:
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- text: "Psychosis-9B-v1"
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output:
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url: https://cdn-uploads.huggingface.co/production/uploads/68e840caa318194c44ec2a04/BDaWz9F6fG9cs6iJWoPcf.png
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---
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> [!CAUTION]
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> <span style="color:red; font-weight:bold">⚠️ Warning:</span> This model can produce narratives and RP that contain violent and graphic erotic content. Adjust your system prompt accordingly. Also, use **Gemma 2** chat template.
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>
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> [!NOTE]
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> <span style="color:red; font-weight:bold">Note:</span> There are two versions of Psychosis:
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> - The regular version is censored and has refusals but might be smarter overall.
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> - The uncensored version does not have refusals, but is partially broken and sometimes outputs chinese.
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>
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# 🧠 Psychosis 9B v1
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This merge was made using the `karcher` method.
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The result is creative, unhinged, and (optionally) uncensored. A truly psycho version of Gemma 2.
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Released in `float32` precision for maximum quality. See the 14B upscale for other versions.
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## Ablation Notes
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The uncensored version was MPOA post-ablated using `scale: 1.5` and `measurement: 31` to all layers.
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**Heretic gemma the writer and ablated components were tested but this resulted in more refusals than ablating after merging.**
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These commands were MPOA formatted ablation (Norm Preserved, Bi-Projected) for maximum uncensored knowledge preservation.
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Unfortunately, using a lower scale of `1.3` did not prevent refusals, but it did prevent chinese output bugs. The `1.5` scale ablation was chosen because it's more uncensored.
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I am releasing **both versions** in case a better ablation method is found later on.
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```
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# python measure.py -m B:\9B\Psychosis-9B-v1 -o B:\9B\Psychosis-9B-v1\ablit_proj --batch-size 8 --projected
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# python analyze_old.py B:\9B\Psychosis-9B-v1\ablit_proj -c
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# sharded_ablate.py psychosis-9b-test2.yml --normpreserve --projected
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```
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