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
| { | |
| "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 | |
| } |