Text Generation
Transformers
Safetensors
English
Spanish
llama
philosophy
reasoning
uncensored
low-refusal
Merge
llama-3
1b
thinkdoc
horror
dark-philosophy
abliterated
antinatalism
pessimism
existential-dread
text-generation-inference
Instructions to use Novaciano/Think-Mad.Doctor-3.2-1B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Novaciano/Think-Mad.Doctor-3.2-1B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Novaciano/Think-Mad.Doctor-3.2-1B")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Novaciano/Think-Mad.Doctor-3.2-1B") model = AutoModelForCausalLM.from_pretrained("Novaciano/Think-Mad.Doctor-3.2-1B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Novaciano/Think-Mad.Doctor-3.2-1B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Novaciano/Think-Mad.Doctor-3.2-1B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Novaciano/Think-Mad.Doctor-3.2-1B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Novaciano/Think-Mad.Doctor-3.2-1B
- SGLang
How to use Novaciano/Think-Mad.Doctor-3.2-1B 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/Think-Mad.Doctor-3.2-1B" \ --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": "Novaciano/Think-Mad.Doctor-3.2-1B", "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 "Novaciano/Think-Mad.Doctor-3.2-1B" \ --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": "Novaciano/Think-Mad.Doctor-3.2-1B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Novaciano/Think-Mad.Doctor-3.2-1B with Docker Model Runner:
docker model run hf.co/Novaciano/Think-Mad.Doctor-3.2-1B
| base_model: UmbrellaInc/Executer-Virus-3.2-1B | |
| merge_method: slerp | |
| dtype: float32 | |
| parameters: | |
| t: 0.7 | |
| # Configuraci贸n para estabilidad en hardware limitado | |
| memory_efficient: true # Procesa capas secuencialmente | |
| low_cpu_mem_usage: true # Reduce uso de RAM durante merge | |
| models: | |
| - model: Novaciano/Prototipo | |
| # Forzar precisi贸n por modelo si es necesario | |
| dtype: float32 | |
| - model: UmbrellaInc/Executer-Virus-3.2-1B | |
| dtype: float32 |