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

Libraries

How to use appvoid/palmer-005-core with Transformers:

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

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

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("appvoid/palmer-005-core")
model = AutoModelForCausalLM.from_pretrained("appvoid/palmer-005-core")
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=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use appvoid/palmer-005-core with vLLM:

Install from pip and serve model

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

Use Docker

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

SGLang

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

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

You need to agree to share your contact information to access this model

This repository is publicly accessible, but you have to accept the conditions to access its files and content.

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, the important distinction is instruction-following text transformations. With only 350m parameters, this model is perfect for experiments on laptops and mobile devices.

	
		
	
	
		prompt
	
There is no prompt intentionally set.

	
		
	
	
		Leaderboard
	
Our custom evaluation consists of 100 text-editing tasks where the model has to modify a diversity of texts in different ways. All models were evaluated using q8_0 gguf quantization.

	
		
Model
Avg
Emb
String
Token
Rule
Exact
Strict
Flagged
Params

🥇 core
88.53
96.56
85.19
82.33
91.14
51/100
75/100
10/100
350m

nano
84.70
95.81
81.12
78.22
87.57
39/100
68/100
19/100
90m

lfm2
72.04
93.19
62.00
56.22
75.35
21/100
40/100
35/100
700m

	
As people already know, leaderboards are not enough, they're just a small light in the right direction. So, if you find its weaknesses, don't hesitate to share them, this way it's ensured a better experience for the whole community.

	
		
	
	
		supporters
	

	
		
	
	
		legal
	
If you are an individual, you're totally free to make money with the model as long as you properly credit the model being used in your products. If you are a company, you need to get a license at this email for commercial purposes.
Note: the model has not been tested as a chat assistant and it might not work as intended, use with caution.

Model	Avg	Emb	String	Token	Rule	Exact	Strict	Flagged	Params
`🥇 core`	88.53	96.56	85.19	82.33	91.14	51/100	75/100	10/100	350m
`nano`	84.70	95.81	81.12	78.22	87.57	39/100	68/100	19/100	90m
`lfm2`	72.04	93.19	62.00	56.22	75.35	21/100	40/100	35/100	700m