Instructions to use appvoid/palmer-003 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use appvoid/palmer-003 with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="appvoid/palmer-003")

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("appvoid/palmer-003")
model = AutoModelForCausalLM.from_pretrained("appvoid/palmer-003", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use appvoid/palmer-003 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 appvoid/palmer-003
# Run inference directly in the terminal:
llama cli -hf appvoid/palmer-003

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf appvoid/palmer-003
# Run inference directly in the terminal:
llama cli -hf appvoid/palmer-003

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 appvoid/palmer-003
# Run inference directly in the terminal:
./llama-cli -hf appvoid/palmer-003

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 appvoid/palmer-003
# Run inference directly in the terminal:
./build/bin/llama-cli -hf appvoid/palmer-003

Use Docker

docker model run hf.co/appvoid/palmer-003

LM Studio
Jan

vLLM

How to use appvoid/palmer-003 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "appvoid/palmer-003"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "appvoid/palmer-003",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/appvoid/palmer-003

SGLang

How to use appvoid/palmer-003 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 "appvoid/palmer-003" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "appvoid/palmer-003",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

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 "appvoid/palmer-003" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "appvoid/palmer-003",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Ollama
How to use appvoid/palmer-003 with Ollama:
```
ollama run hf.co/appvoid/palmer-003
```
Unsloth Desktop
Docker Model Runner
How to use appvoid/palmer-003 with Docker Model Runner:
```
docker model run hf.co/appvoid/palmer-003
```

Lemonade

How to use appvoid/palmer-003 with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull appvoid/palmer-003

Run and chat with the model

lemonade run user.palmer-003-{{QUANT_TAG}}

List all available models

lemonade list

Atomic Chat

appvoid commited on Jan 27, 2024

Commit

4836fa5

verified ·

1 Parent(s): 4011f8b

Create README.md

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+---
+license: apache-2.0
+language:
+- en
+- es
+- fr
+tags:
+- merge
+---
+![palmer-003 logo](https://huggingface.co/appvoid/palmer-002.5/resolve/main/003.png)
+Creative writing has never been so accesible, palmer goes beyond what it was thought about small language models. This model is a "MErging of Experts" (MEoE) using an internal model `palmer-003` as base, biased as an assistant, using dpo technique, without using any prompts—as a result of these efforts—palmer is better than most 1b language models on most benchmarks, despite being sometimes 40% smaller than its counterparts.
+```
+	              MMLU     ARC-C    OBQA   HellaSwag  PIQA  Winogrande Average  Parameters
+tinyllama      | 0.2577 | 0.3029 | 0.3600 | 0.5935 | 0.7329 | 0.5959 | 0.4738 | 1.1B       |
+zyte 	       | 0.2397 | 0.3353 | 0.3700 | 0.6086 | 0.7541 | 0.5998 | 0.4845 | 1.1B       |
+palmer         | 0.2523 | 0.3439 | 0.3740 | 0.6208 | 0.7524 | 0.6590 | 0.5004 | 1.1B       |
+qwen           | 0.4536 | 0.3490 | 0.3320 | 0.5876 | 0.7307 | 0.5896 | 0.5070 | 1.8B       |
+```
+This work constitutes, given its compactness, an advancement towards SMLs, easily empowering edge devices such as mobile phones, raspberry pis and automated software/robots. Aditionally, palmer-002.5 deviates its main philosophy from palmer-family to become a more powerful model with more data instead of less.
+```
+prompt: Reality is but
+output: a dream,
+And the dreams we make are our reality.
+The world is a canvas, painted by our minds,
+And we can make it a masterpiece.
+So let us create, let us dream,
+And let our imagination run wild.
+For in our imagination lies our power,
+To create a world that is truly our own.
+```
+You can support me [through kofi](https://ko-fi.com/appvoid)
+Note that since this model uses a transformer architecture as any popular language model, its output sometimes contains hallucinations (make mistakes or false statements), and as such, it must be used with caution on sensitive scenarios.