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
File size: 1,372 Bytes
9b51f42 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 | {
"version": "1.0",
"truncation": null,
"padding": null,
"added_tokens": [],
"normalizer": null,
"pre_tokenizer": {
"type": "Split",
"pattern": {
"Regex": "[\\s\\S]"
},
"behavior": "Isolated",
"invert": false
},
"post_processor": null,
"decoder": {
"type": "Fuse"
},
"model": {
"type": "WordLevel",
"vocab": {
"\n": 0,
" ": 1,
"!": 2,
"$": 3,
"&": 4,
"'": 5,
",": 6,
"-": 7,
".": 8,
"3": 9,
":": 10,
";": 11,
"?": 12,
"A": 13,
"B": 14,
"C": 15,
"D": 16,
"E": 17,
"F": 18,
"G": 19,
"H": 20,
"I": 21,
"J": 22,
"K": 23,
"L": 24,
"M": 25,
"N": 26,
"O": 27,
"P": 28,
"Q": 29,
"R": 30,
"S": 31,
"T": 32,
"U": 33,
"V": 34,
"W": 35,
"X": 36,
"Y": 37,
"Z": 38,
"a": 39,
"b": 40,
"c": 41,
"d": 42,
"e": 43,
"f": 44,
"g": 45,
"h": 46,
"i": 47,
"j": 48,
"k": 49,
"l": 50,
"m": 51,
"n": 52,
"o": 53,
"p": 54,
"q": 55,
"r": 56,
"s": 57,
"t": 58,
"u": 59,
"v": 60,
"w": 61,
"x": 62,
"y": 63,
"z": 64
},
"unk_token": "<unk>"
}
} |