Text Generation
Transformers
Safetensors
busybeaver_qdelta
busybeaver
tool-calling
agent-policy
json
local-agents
qdelta
50m
Instructions to use GestaltLabs/BusyBeaver-50M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GestaltLabs/BusyBeaver-50M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="GestaltLabs/BusyBeaver-50M")# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("GestaltLabs/BusyBeaver-50M", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use GestaltLabs/BusyBeaver-50M with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "GestaltLabs/BusyBeaver-50M" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "GestaltLabs/BusyBeaver-50M", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/GestaltLabs/BusyBeaver-50M
- SGLang
How to use GestaltLabs/BusyBeaver-50M 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 "GestaltLabs/BusyBeaver-50M" \ --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": "GestaltLabs/BusyBeaver-50M", "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 "GestaltLabs/BusyBeaver-50M" \ --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": "GestaltLabs/BusyBeaver-50M", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use GestaltLabs/BusyBeaver-50M with Docker Model Runner:
docker model run hf.co/GestaltLabs/BusyBeaver-50M
File size: 626 Bytes
32f947d | 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 | {
"architectures": [
"BusyBeaverQDeltaForCausalLM"
],
"conv_kernel_size": 4,
"dtype": "float32",
"hidden_size": 384,
"initializer_range": 0.02,
"intermediate_size": 1152,
"layer_pattern": [
"delta",
"delta",
"delta",
"attention"
],
"max_position_embeddings": 2048,
"model_type": "busybeaver_qdelta",
"mtp_steps": 2,
"num_attention_heads": 6,
"num_hidden_layers": 16,
"num_key_value_heads": 2,
"num_tool_families": 8,
"rms_norm_eps": 1e-06,
"rope_theta": 1000000.0,
"transformers_version": "4.57.6",
"use_mtp": true,
"use_router_aux": true,
"vocab_size": 16384
}
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