Instructions to use appvoid/palmer-005 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use appvoid/palmer-005 with Transformers:

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

pipe = pipeline("text-generation", model="appvoid/palmer-005")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

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

tokenizer = AutoTokenizer.from_pretrained("appvoid/palmer-005")
model = AutoModelForCausalLM.from_pretrained("appvoid/palmer-005", device_map="auto")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=256)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use appvoid/palmer-005 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "appvoid/palmer-005"
# 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-005",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/appvoid/palmer-005

SGLang

How to use appvoid/palmer-005 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-005" \
    --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-005",
		"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-005" \
        --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-005",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use appvoid/palmer-005 with Docker Model Runner:
```
docker model run hf.co/appvoid/palmer-005
```

appvoid commited on May 13

Commit

73ef7de

verified ·

1 Parent(s): fdabbf5

Update README.md

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@@ -10,12 +10,63 @@ tags:
 private: true
 ---
-![logo](https://huggingface.co/appvoid/palmer-005-nano/resolve/main/palmer-005-icon.png)
-## Intended use
-Fifth generation of general-purpose palmer series: better foundational models, better data, same tasks: Text rewriting, paraphrasing, tone transfer, grammar-style editing, and instruction-following text transformations. With only 90m parameters, this model is perfect for experiments on small SBCs and low-power devices.
-## Prompt
-None

 private: true
 ---
+<style>
+  @import url('https://fonts.googleapis.com/css2?family=Roboto:ital,wght@0,100..900;1,100..900&display=swap');
+  *, html, body, div {
+    color: white;
+    background: black !important;
+    border: none;
+    font-family: "Roboto", sans-serif !important;
+    font-optical-sizing: auto;
+    font-weight: 300;
+    font-style: normal;
+    font-variation-settings: "wdth" 100;
+  }
+  img {
+    filter: contrast(1.3);
+    user-select: none;
+    transition: all 0.2s ease;
+    border-radius: .5rem;
+    display: block !important;
+    margin: 1rem auto !important;
+  }
+  img:hover {
+    transform: rotate(1deg);
+    filter: invert(100%) contrast(0.8) hue-rotate(270deg);
+  }
+  h1,h2,h3,h4,h5,h6,a {
+      font-weight: 600;
+  }
+</style>
+<body>
+<div style="background-color: transparent; border-radius: .5rem; padding: 2rem; font-family: monospace; font-size: 1.15rem; text-align: justify;">
+<p align="center">
+<img src="https://huggingface.co/appvoid/palmer-005-nano/resolve/main/palmer-005-icon.png" alt="cubby">
+</p>
+In this repository, we propose the next iteration of `palmer`, a new family of small language models trained with better foundational models, better data but same tasks: Text rewriting, paraphrasing, tone transfer, grammar-style editing, and instruction-following text transformations. With only 90m parameters, this model is perfect for experiments on small SBCs and low-power devices. Now with `lfm` and `falcon-h1` as main as the base architectures for improvements.
+#### prompt
+There is no prompt intentionally set.
+#### strengths
+- Strong instruction-following bias
+- Excellent classifiers
+#### limitations
+- Poor causality understanding
+- Hallucinations
+#### supporters
+<a href="https://ko-fi.com/appvoid" target="_blank"><img src="https://cdn.buymeacoffee.com/buttons/v2/default-yellow.png" alt="Buy Me A Coffee" style="height: 34px !important; margin-top: -4px;width: 128px !important; filter: contrast(2) grayscale(100%) brightness(100%);" ></a>
+**Note**: the model has not been tested as a chat assistant and it might not work as intended, use with caution.
+</div>
+</body>