Text Generation
Transformers
Safetensors
English
gpt-s2.5
tiny
tiny-lm
tiny-model
slm
small-language-model
from-scratch
gpt
gqa
swiglu
rope
rmsnorm
cpu-trained
Instructions to use Compactbot/compacttest-5m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Compactbot/compacttest-5m with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Compactbot/compacttest-5m")# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("Compactbot/compacttest-5m", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Compactbot/compacttest-5m with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Compactbot/compacttest-5m" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Compactbot/compacttest-5m", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Compactbot/compacttest-5m
- SGLang
How to use Compactbot/compacttest-5m 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 "Compactbot/compacttest-5m" \ --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": "Compactbot/compacttest-5m", "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 "Compactbot/compacttest-5m" \ --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": "Compactbot/compacttest-5m", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Compactbot/compacttest-5m with Docker Model Runner:
docker model run hf.co/Compactbot/compacttest-5m
File size: 530 Bytes
0747e94 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | {
"architectures": [
"GPTS25ForCausalLM"
],
"model_type": "gpt-s2.5",
"vocab_size": 8192,
"hidden_size": 256,
"num_hidden_layers": 4,
"num_attention_heads": 8,
"num_key_value_heads": 2,
"head_dim": 32,
"intermediate_size": 768,
"max_position_embeddings": 512,
"rope_theta": 10000.0,
"norm_type": "rmsnorm",
"norm_eps": 1e-06,
"mlp_activation": "swiglu",
"tie_word_embeddings": true,
"bias": false,
"torch_dtype": "float32",
"transformers_version": "4.50.0",
"parameter_count": 5114112
} |