Model Card for Model ID
Model Details
Model Description
Removing 26 layers from RefalMachine/RuadaptQwen3-4B-Instruct === Parameters: 4,007,937,536 Layers: 36
--- Original Model Generation --- Prompt: 'Paris is the capital of' Generated: Paris is the capital of France and one of the world's most visited cities, attracting over 22 million tourists annually. It is renowned for its rich history, iconic landmarks, and vibrant cultural scene. Located in the north-central part of metropolitan France
Prompt: 'The theory of relativity states that' Generated: The theory of relativity states that the speed of light in a vacuum is constant for all observers, regardless of their motion or the motion of the light source. However, when light travels through a medium such as water or glass, its speed decreases.
Removing layers: 100%|██████████| 36/36 [00:00<00:00, 235194.62it/s] --- Pruned Model: RefalMachine/RuadaptQwen3-4B-Instruct Parameters: 1,383,736,320 Layers: 10
--- Pruning Results --- Parameter reduction: 2,624,201,216 (65.48%) Layer reduction: 26 layers (72.22%)
--- Pruned Model Generation ---
Prompt: 'Paris is the capital of' Generated: Paris is the capital ofmindlessamenterics getArguments argumentsстаходходсякаясясякийкийломовскийowskiowskiкуроновavirus pandemic pandemicінийскийскийскомановсяkosсяскойскомскийломецкийばшиестьяжиковикованов
Prompt: 'The theory of relativity states that' Generated: The theory of relativity states thatophys physicists physicistsэнсяENCEScapeable measurable measurableizableizable Technologiescape знанияведенияведениячинстваствоствастваствутуKENkenohanaотовкаясяся......
?
?(fulnessfulamentericsallymenteamente Swal Swal
Example 1 completed! Parameter reduction: 65.48%
DEPTH PRUNING RESULTS SUMMARY
Model Method Param Reduction Layers Removed
RefalMachine/RuadaptQwen3-4B-Instruct Layer Count 65.48 % 26/36
RefalMachine/RuadaptQwen3-4B-Instruct Percentage 70.51 % 28/36
Total examples tested: 2 Depth pruning examples completed successfully!
- Developed by: [More Information Needed]
- Funded by [optional]: [More Information Needed]
- Shared by [optional]: [More Information Needed]
- Model type: [More Information Needed]
- Language(s) (NLP): [More Information Needed]
- License: [More Information Needed]
- Finetuned from model [optional]: [More Information Needed]
Model Sources [optional]
- Repository: [More Information Needed]
- Paper [optional]: [More Information Needed] Apache 2, same as https://github.com/peremartra/optipfair
- Demo [optional]: [More Information Needed]
Uses
Direct Use
[More Information Needed]
Downstream Use [optional]
[More Information Needed]
Out-of-Scope Use
[More Information Needed]
Bias, Risks, and Limitations
[More Information Needed]
Recommendations
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
How to Get Started with the Model
Use the code below to get started with the model.
[More Information Needed]
Training Details
Training Data
[More Information Needed]
Training Procedure
Preprocessing [optional]
[More Information Needed]
Training Hyperparameters
- Training regime: [More Information Needed]
Speeds, Sizes, Times [optional]
[More Information Needed]
Evaluation
Testing Data, Factors & Metrics
Testing Data
[More Information Needed]
Factors
[More Information Needed]
Metrics
[More Information Needed]
Results
[More Information Needed]
Summary
Model Examination [optional]
[More Information Needed]
Environmental Impact
Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).
- Hardware Type: [More Information Needed]
- Hours used: [More Information Needed]
- Cloud Provider: [More Information Needed]
- Compute Region: [More Information Needed]
- Carbon Emitted: [More Information Needed]
Technical Specifications [optional]
Model Architecture and Objective
[More Information Needed]
Compute Infrastructure
[More Information Needed]
Hardware
[More Information Needed]
Software
[More Information Needed]
Citation [optional]
BibTeX:
[More Information Needed]
APA:
[More Information Needed]
Glossary [optional]
[More Information Needed]
More Information [optional]
[More Information Needed]
Model Card Authors [optional]
[More Information Needed]
Model Card Contact
[More Information Needed]