Instructions to use aethertp/PicoLM-V3-Pro-82M-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-V3-Pro-82M-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-V3-Pro-82M-Instruct:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf aethertp/PicoLM-V3-Pro-82M-Instruct:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf aethertp/PicoLM-V3-Pro-82M-Instruct:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf aethertp/PicoLM-V3-Pro-82M-Instruct:Q4_K_M

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-V3-Pro-82M-Instruct:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf aethertp/PicoLM-V3-Pro-82M-Instruct:Q4_K_M

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-V3-Pro-82M-Instruct:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf aethertp/PicoLM-V3-Pro-82M-Instruct:Q4_K_M

Use Docker

docker model run hf.co/aethertp/PicoLM-V3-Pro-82M-Instruct:Q4_K_M

LM Studio
Jan

vLLM

How to use aethertp/PicoLM-V3-Pro-82M-Instruct with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "aethertp/PicoLM-V3-Pro-82M-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-V3-Pro-82M-Instruct",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/aethertp/PicoLM-V3-Pro-82M-Instruct:Q4_K_M

Ollama
How to use aethertp/PicoLM-V3-Pro-82M-Instruct with Ollama:
```
ollama run hf.co/aethertp/PicoLM-V3-Pro-82M-Instruct:Q4_K_M
```
Unsloth Desktop
Docker Model Runner
How to use aethertp/PicoLM-V3-Pro-82M-Instruct with Docker Model Runner:
```
docker model run hf.co/aethertp/PicoLM-V3-Pro-82M-Instruct:Q4_K_M
```

Lemonade

How to use aethertp/PicoLM-V3-Pro-82M-Instruct with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull aethertp/PicoLM-V3-Pro-82M-Instruct:Q4_K_M

Run and chat with the model

lemonade run user.PicoLM-V3-Pro-82M-Instruct-Q4_K_M

List all available models

lemonade list

Atomic Chat

PicoLM-V3-Pro-82M-Instruct / tokenizer_config.json

aethertp

Initial verified release: safetensors + modeling + tokenizer (4K YaRN)

4db2d6b verified 4 days ago

Raw History Blame Contribute Delete

476 Bytes

	{
	"backend": "tokenizers",
	"bos_token": "<\|endoftext\|>",
	"clean_up_tokenization_spaces": false,
	"eos_token": "<\|im_end\|>",
	"model_max_length": 1000000000000000019884624838656,
	"pad_token": "<\|pad\|>",
	"tokenizer_class": "TokenizersBackend",
	"chat_template": "{% for message in messages %}{{'<\|im_start\|>' + message['role'] + '\n' + message['content'] + '<\|im_end\|>' + '\n'}}{% endfor %}{% if add_generation_prompt %}{{ '<\|im_start\|>assistant\n' }}{% endif %}"
	}