Text Generation
Transformers
Safetensors
tinyqwen3_novelty
qwen3
causal-lm
tiny-language-model
novelty-gated-attention
trust-remote-code
custom_code
Instructions to use User01110/tinyLM-8M-exp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use User01110/tinyLM-8M-exp with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="User01110/tinyLM-8M-exp", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("User01110/tinyLM-8M-exp", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use User01110/tinyLM-8M-exp with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "User01110/tinyLM-8M-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/tinyLM-8M-exp", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/User01110/tinyLM-8M-exp
- SGLang
How to use User01110/tinyLM-8M-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/tinyLM-8M-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/tinyLM-8M-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/tinyLM-8M-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/tinyLM-8M-exp", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use User01110/tinyLM-8M-exp with Docker Model Runner:
docker model run hf.co/User01110/tinyLM-8M-exp
File size: 442 Bytes
3bc1fd6 c2033fb 3bc1fd6 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | {
"add_prefix_space": true,
"backend": "tokenizers",
"bos_token": "<bos>",
"clean_up_tokenization_spaces": false,
"eos_token": "<eos>",
"is_local": false,
"local_files_only": false,
"model_max_length": 1000000000,
"pad_token": "<eos>",
"tokenizer_class": "PreTrainedTokenizerFast",
"unk_token": "<unk>",
"vocab_size": 4096,
"additional_special_tokens": [
"<|im_start|>",
"<|im_end|>"
]
}
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