Text Generation
Transformers
Safetensors
English
llama
nanodex
tiny-lm
pretrained-from-scratch
text-generation-inference
Instructions to use SLM-Archive/LowOnMind-8M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SLM-Archive/LowOnMind-8M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="SLM-Archive/LowOnMind-8M")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("SLM-Archive/LowOnMind-8M") model = AutoModelForCausalLM.from_pretrained("SLM-Archive/LowOnMind-8M", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use SLM-Archive/LowOnMind-8M with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "SLM-Archive/LowOnMind-8M" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "SLM-Archive/LowOnMind-8M", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/SLM-Archive/LowOnMind-8M
- SGLang
How to use SLM-Archive/LowOnMind-8M 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 "SLM-Archive/LowOnMind-8M" \ --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": "SLM-Archive/LowOnMind-8M", "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 "SLM-Archive/LowOnMind-8M" \ --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": "SLM-Archive/LowOnMind-8M", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use SLM-Archive/LowOnMind-8M with Docker Model Runner:
docker model run hf.co/SLM-Archive/LowOnMind-8M
Download model.safetensors from SLM-Archive/LowOnMind-8M: direct link, hf CLI and curl.
- Browser
- Download file 32.2 MB
-
https://huggingface.co/SLM-Archive/LowOnMind-8M/resolve/main/model.safetensors
- Command line
-
hf download hf://SLM-Archive/LowOnMind-8M/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/SLM-Archive/LowOnMind-8M/resolve/main/model.safetensors
32.2 MB
- Xet hash:
- aa16e0d3885aa6d96b2fbfd3a4b48d129cfc4e43d2f3202b06db09cda62d5ddc
- Size of remote file:
- 32.2 MB
- SHA256:
- ba1df7576bd7a53279bf6effcb4b621fa211f36ac3be342a669e9606989c1a85
路
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