Text Generation
Transformers
Safetensors
English
flygpt
connectome
fruit-fly
drosophila
malecns
recurrent
sparse
tiny-shakespeare
custom_code
Instructions to use QuixiAI/FlyGPT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use QuixiAI/FlyGPT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="QuixiAI/FlyGPT", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("QuixiAI/FlyGPT", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use QuixiAI/FlyGPT with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "QuixiAI/FlyGPT" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "QuixiAI/FlyGPT", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/QuixiAI/FlyGPT
- SGLang
How to use QuixiAI/FlyGPT 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 "QuixiAI/FlyGPT" \ --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": "QuixiAI/FlyGPT", "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 "QuixiAI/FlyGPT" \ --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": "QuixiAI/FlyGPT", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use QuixiAI/FlyGPT with Docker Model Runner:
docker model run hf.co/QuixiAI/FlyGPT
| { | |
| "model_type": "flygpt", | |
| "architectures": [ | |
| "FlyGPTForCausalLM" | |
| ], | |
| "auto_map": { | |
| "AutoConfig": "configuration_flygpt.FlyGPTConfig", | |
| "AutoModelForCausalLM": "modeling_flygpt.FlyGPTForCausalLM" | |
| }, | |
| "vocab_size": 65, | |
| "num_neurons": 5000, | |
| "num_edges": 524324, | |
| "embedding_dim": 32, | |
| "num_input_neurons": 256, | |
| "num_output_neurons": 512, | |
| "microsteps": 2, | |
| "activation": "tanh", | |
| "learned_leak": true, | |
| "leak_init": 0.5, | |
| "degree_normalization": true, | |
| "init_scale": 1.0, | |
| "dtype": "bfloat16", | |
| "training_steps": 100000, | |
| "graph": { | |
| "graph_name": "cb5k", | |
| "condition": "real", | |
| "control_seed": 1, | |
| "source": "malecns-v1.0", | |
| "region_filter": "central_brain", | |
| "min_synapses": 3, | |
| "hash": "f82b783b7ccb5a354fc4cf3de6de4a98d75029303c55f8faae28ab807828a007" | |
| }, | |
| "training_state": { | |
| "status": "init", | |
| "condition": "real", | |
| "seed": 1, | |
| "project": "flygpt-v0-100k" | |
| } | |
| } |