Instructions to use aethertp/PicoLM-80M-Instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use aethertp/PicoLM-80M-Instruct with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf aethertp/PicoLM-80M-Instruct
# Run inference directly in the terminal:
llama cli -hf aethertp/PicoLM-80M-Instruct

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf aethertp/PicoLM-80M-Instruct
# Run inference directly in the terminal:
llama cli -hf aethertp/PicoLM-80M-Instruct

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf aethertp/PicoLM-80M-Instruct
# Run inference directly in the terminal:
./llama-cli -hf aethertp/PicoLM-80M-Instruct

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf aethertp/PicoLM-80M-Instruct
# Run inference directly in the terminal:
./build/bin/llama-cli -hf aethertp/PicoLM-80M-Instruct

Use Docker

docker model run hf.co/aethertp/PicoLM-80M-Instruct

LM Studio
Jan

vLLM

How to use aethertp/PicoLM-80M-Instruct with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "aethertp/PicoLM-80M-Instruct"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "aethertp/PicoLM-80M-Instruct",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/aethertp/PicoLM-80M-Instruct

Ollama
How to use aethertp/PicoLM-80M-Instruct with Ollama:
```
ollama run hf.co/aethertp/PicoLM-80M-Instruct
```
Unsloth Desktop
Docker Model Runner
How to use aethertp/PicoLM-80M-Instruct with Docker Model Runner:
```
docker model run hf.co/aethertp/PicoLM-80M-Instruct
```

Lemonade

How to use aethertp/PicoLM-80M-Instruct with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull aethertp/PicoLM-80M-Instruct

Run and chat with the model

lemonade run user.PicoLM-80M-Instruct-{{QUANT_TAG}}

List all available models

lemonade list

Atomic Chat

PicoLM-80M-Instruct

File size: 413 Bytes

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{
  "architectures": [
    "LlamaForCausalLM"
  ],
  "model_type": "llama",
  "vocab_size": 16384,
  "hidden_size": 576,
  "num_hidden_layers": 20,
  "num_attention_heads": 9,
  "num_key_value_heads": 3,
  "intermediate_size": 1536,
  "max_position_embeddings": 2048,
  "rms_norm_eps": 1e-05,
  "rope_theta": 10000.0,
  "tie_word_embeddings": true,
  "torch_dtype": "float16",
  "transformers_version": "4.45.0"
}