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

Llama new
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

aethertp commited on 22 days ago

Commit

02a7e68

verified ·

1 Parent(s): 7573418

Upload config.json with huggingface_hub

Browse files

Files changed (1) hide show

config.json +6 -1

config.json CHANGED Viewed

@@ -7,13 +7,17 @@
   "vocab_size": 24576,
   "emb_dim": 128,
   "dim": 576,
   "n_layers": 21,
   "layer_repeat": 2,
   "n_heads": 9,
   "n_kv_heads": 3,
   "head_dim": 64,
   "intermediate_dim": 1664,
-  "max_seq_len": 2048,
   "orig_seq_len": 2048,
   "norm_eps": 1e-05,
   "rope_theta": 10000.0,
@@ -21,6 +25,7 @@
   "eos_token_id": 2,
   "pad_token_id": 3,
   "tie_word_embeddings": true,
   "architectures": [
     "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,
   "eos_token_id": 2,
   "pad_token_id": 3,
   "tie_word_embeddings": true,
+  "use_cache": false,
   "architectures": [
     "PicoLMV3ForCausalLM"
   ]