Optimize Weight Rounding via Signed Gradient Descent for the Quantization of LLMs
Paper • 2309.05516 • Published • 12
llm.create_chat_completion(
messages = "No input example has been defined for this model task."
)Model Details
This model is a gguf q4km of google/gemma-4-31B-it generated by intel/auto-round. Please follow the license of the original model.
Llamacpp inference
llama-cli -m ./gemma-4-31B-it-Q4_K_M.gguf --mmproj .mmproj-model.gguf
Loaded media from 'demo.jpeg'
what's in the image
[Start thinking] Here's a thinking process that leads to the description:
Analyze the Request: The user has provided an image and asked "what's in the image". This requires a comprehensive description of the visual elements.
Initial Scan (The Big Picture):
- Main subjects: A dog and a person.
- Setting: A beach at sunset/sunrise.
- Action: The dog is "shaking hands" or giving a paw to the person.
- Mood: Warm, peaceful, affectionate.
Detailed Breakdown (Breaking it down into components):
The Person:
- Gender/Appearance: A young woman with long dark hair.
- Expression: Smiling, looking at the dog.
- Clothing: Plaid/checkered button-down shirt (dark blue/grey and white), dark pants/leggings.
- Pose: Sitting on the sand, legs bent, interacting with the dog.
The Dog:
- Breed/Type: Looks like a yellow Labrador Retriever.
- Color: Pale yellow/cream.
- Pose: Sitting upright, facing the woman, lifting its right paw to meet her hand.
- Gear: Wearing a blue and red harness. There's a red leash lying on the sand behind it.
The Setting (Background & Environment):
- Foreground: Sandy beach with some footprints and texture.
- Midground: The shoreline where waves are gently breaking.
- Background: The ocean stretching to the horizon.
- Lighting/Sky: The sun is low (either sunrise or sunset), creating a warm, golden glow coming from the right side of the frame. The sky is bright and almost washed out due to the light.
Synthesize and Structure the Description:
- Start with a high-level summary: A heartwarming scene of a woman and her dog on a beach during a golden hour.
- Describe the main interaction: The woman is sitting on the sand, and her yellow Labrador is sitting in front of her, offering its paw for her to hold.
- Add details about the woman: Mention her long dark hair, smiling expression, and plaid shirt.
- Add details about the dog: Mention the breed (Labrador), the harness it's wearing, and the leash on the sand.
- Describe the environment: Detail the sandy beach, the ocean waves, and the bright, warm light of the setting or rising sun.
- Conclude with the overall mood: Mention the peaceful and affectionate atmosphere.
Final Review: Read through the generated description while looking at the image to ensure accuracy and completeness. (Self-correction: Ensure I mention the lighting specifically, as it's a key part of the mood). [End thinking]
This image shows a heartwarming scene of a woman and her dog on a sandy beach during the "golden hour" (either sunrise or sunset).
Here are the details:
- The Subjects: A young woman with long dark hair is sitting on the sand, smiling at her dog. She is wearing a dark plaid button-down shirt and dark pants. Facing her is a yellow Labrador Retriever sitting upright. The dog is wearing a blue and red harness and is lifting its right paw to "shake hands" with the woman. A red leash lies on the sand behind the dog.
- The Setting: They are on a wide, sandy beach. In the background, the ocean is visible with gentle waves breaking on the shore.
- Lighting and Mood: The sun is low on the horizon (to the right), casting a warm, bright golden light across the scene and creating a peaceful, affectionate atmosphere. The sky is very bright, almost white, due to the intensity of the light.
Generate the Model
auto-round
google/gemma-4-31B-it
--output_dir
"./quantized"
--iters 0
--format "gguf:q4_k_m"
Ethical Considerations and Limitations
The model can produce factually incorrect output, and should not be relied on to produce factually accurate information. Because of the limitations of the pretrained model and the finetuning datasets, it is possible that this model could generate lewd, biased or otherwise offensive outputs.
Therefore, before deploying any applications of the model, developers should perform safety testing.
Caveats and Recommendations
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model.
Here are a couple of useful links to learn more about Intel's AI software:
Disclaimer
The license on this model does not constitute legal advice. We are not responsible for the actions of third parties who use this model. Please consult an attorney before using this model for commercial purposes.
Cite
@article{cheng2023optimize, title={Optimize weight rounding via signed gradient descent for the quantization of llms}, author={Cheng, Wenhua and Zhang, Weiwei and Shen, Haihao and Cai, Yiyang and He, Xin and Lv, Kaokao and Liu, Yi}, journal={arXiv preprint arXiv:2309.05516}, year={2023} }
- Downloads last month
- 80
Hardware compatibility
Log In to add your hardware
4-bit
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="Intel/gemma-4-31B-it-q4km-AutoRound-preview", filename="", )