Text Generation
Transformers
Safetensors
gpt2
tiny
tiny-lm
small-language-model
subword
bpe
from-scratch
tinystories
charlm
7m-params
text-generation-inference
Instructions to use Compactbot/subword-gpt-7m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Compactbot/subword-gpt-7m with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Compactbot/subword-gpt-7m")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, GPT tokenizer = AutoTokenizer.from_pretrained("Compactbot/subword-gpt-7m") model = GPT.from_pretrained("Compactbot/subword-gpt-7m", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Compactbot/subword-gpt-7m with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Compactbot/subword-gpt-7m" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Compactbot/subword-gpt-7m", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Compactbot/subword-gpt-7m
- SGLang
How to use Compactbot/subword-gpt-7m 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/subword-gpt-7m" \ --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/subword-gpt-7m", "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/subword-gpt-7m" \ --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/subword-gpt-7m", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Compactbot/subword-gpt-7m with Docker Model Runner:
docker model run hf.co/Compactbot/subword-gpt-7m
File size: 324 Bytes
093384d | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | {
"architectures": ["GPT"],
"vocab_size": 8192,
"n_layer": 6,
"n_head": 8,
"n_embd": 256,
"n_inner": 1024,
"n_positions": 512,
"tie_word_embeddings": true,
"bias": false,
"norm": "rmsnorm",
"activation": "gelu",
"torch_dtype": "bfloat16",
"model_type": "gpt2",
"transformers_version": "4.40.0"
}
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