Text Generation
Transformers
Safetensors
English
swa_lm
custom_code
small-language-model
hybrid-attention
sliding-window-attention
muon
Instructions to use User01110/100M-exp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use User01110/100M-exp with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="User01110/100M-exp", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("User01110/100M-exp", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use User01110/100M-exp with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "User01110/100M-exp" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "User01110/100M-exp", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/User01110/100M-exp
- SGLang
How to use User01110/100M-exp 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 "User01110/100M-exp" \ --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": "User01110/100M-exp", "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 "User01110/100M-exp" \ --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": "User01110/100M-exp", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use User01110/100M-exp with Docker Model Runner:
docker model run hf.co/User01110/100M-exp
File size: 653 Bytes
26c5153 | 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 | {
"architectures": [
"SWAForCausalLM"
],
"auto_map": {
"AutoConfig": "modeling_swa.SWAConfig",
"AutoModelForCausalLM": "modeling_swa.SWAForCausalLM"
},
"bos_token_id": 1,
"conv": 4,
"d": 576,
"dtype": "bfloat16",
"eos_token_id": 2,
"full": [
6,
14
],
"h": 9,
"hd": 64,
"hidden_size": 576,
"hope": true,
"kv": 3,
"l": 20,
"m": 1792,
"max_position_embeddings": 8192,
"model_type": "swa_lm",
"num_hidden_layers": 20,
"pad_token_id": 2,
"seq": 8192,
"theta": 10000.0,
"tie_word_embeddings": true,
"transformers_version": "5.14.1",
"v": 32000,
"vocab_size": 32000,
"window": 512
} |