Text Generation
Transformers
Safetensors
falcon_h1
text-editing
rewriting
paraphrasing
instruct
conversational
Instructions to use appvoid/palmer-005 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
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)# 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=40) 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
File size: 3,753 Bytes
a8549df d7ae277 1082152 23d914e a8549df 73ef7de a8549df 73ef7de 3b0d2d1 73ef7de a8549df 9425904 93a63d8 7291804 9425904 7291804 4340f7f c7c3559 7291804 f2c9ed7 73ef7de 39654e5 f6aae29 39654e5 374e882 73ef7de | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 | ---
base_model: appvoid/graphite-004
library_name: transformers
tags:
- text-generation
- text-editing
- rewriting
- paraphrasing
- instruct
private: true
license: other
datasets:
- appvoid/rewrite
pipeline_tag: text-generation
extra_gated_prompt: "You agree to not use this model (or future versions) to conduct experiments that cause harm to any person or group and to respect the LICENSE that comes with this repository."
extra_gated_fields:
Company: text
Country: country
Specific date: date_picker
I want to use this model for:
type: select
options:
- Research
- Education
- Hobby
- Commercial
- label: Other
value: other
I agree to use this model in good faith ONLY: checkbox
---
<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.
> 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 |
|---:|---|---:|---:|---:|---:|---:|---:|---:|---|
| `🥇 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 |
| `granite4` | 71.96 | 92.54 | 65.01 | 54.98 | 76.41 | 17/100 | 34/100 | 33/100 | 350m |
|`qwen3` | 51.81 | 87.76 | 45.26 | 33.65 | 50.80 | 6/100 | 22/100 | 60/100 | 600m |
The model has learned from a dataset with about 1 million examples on how to edit text in many different ways. The dataset contains high-quality data that was further expanded using common well-known heuristics.
#### 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>
#### 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](mailto:nosoyhackercodigo@gmail.com) for commercial purposes.
> **Note**: the model has not been tested as a chat assistant and it might not work as intended, use with caution.
</div>
</body> |