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 / config.json

aethertp

Upload config.json with huggingface_hub

02a7e68 verified 5 days ago

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722 Bytes

	{
	"model_type": "picolm_v3",
	"auto_map": {
	"AutoConfig": "configuration_picolm_v3.PicoLMV3Config",
	"AutoModelForCausalLM": "modeling_picolm_v3.PicoLMV3ForCausalLM"
	},
	"vocab_size": 24576,
	"emb_dim": 128,
	"dim": 576,
	"hidden_size": 576,
	"n_layers": 21,
	"num_hidden_layers": 21,
	"layer_repeat": 2,
	"n_heads": 9,
	"num_attention_heads": 9,
	"n_kv_heads": 3,
	"num_key_value_heads": 3,
	"head_dim": 64,
	"intermediate_dim": 1664,
	"max_seq_len": 4096,
	"orig_seq_len": 2048,
	"norm_eps": 1e-05,
	"rope_theta": 10000.0,
	"bos_token_id": 0,
	"eos_token_id": 2,
	"pad_token_id": 3,
	"tie_word_embeddings": true,
	"use_cache": false,
	"architectures": [
	"PicoLMV3ForCausalLM"
	]
	}