petergilani
/

Qwen3-Coder-Next-3bit-g128

@@ -1,294 +1,9 @@
 ---
-base_model: Qwen/Qwen3-Coder-Next
-language: en
-library_name: mlx-lm
 license: apache-2.0
-model_name: Qwen3-Coder-Next-3bit-g128
 tags:
-- quantization
-- g128
-- text-generation
-- mlx-lm
 ---
-# Model Card for Model ID
-<!-- Provide a quick summary of what the model is/does. -->
-## Model Details
-### Model Description
-<!-- Provide a longer summary of what this model is. -->
-# Model Card for Qwen3-Coder-Next-3bit-g128
-Quantized Qwen/Qwen3-Coder-Next using mlx-lm to 3-bit with group_size 128 for main weights and fine-grained group_size 64 for MoE weights, with the aim of optimizing accuracy for 3bit quantization.
-## Evaluation Results
-Testing with mlx_lm.evaluate using mmlu_pro with 50 Qs for each topic across all quantization levels.
-### Full Quantization Spectrum Comparison
-| Domain | 3-bit default | 3-bit g128 | 4-bit default | 4-bit g128 | 6-bit default | 6-bit g128 | 8-bit default | 8-bit g128 |
-|---|---|---|---|---|---|---|---|---|
-| Math | 0.94 | 0.90 | 0.92 | 0.92 | 0.90 | 0.94 | 0.92 | 0.94 |
-| Computer Science | 0.82 | 0.84 | 0.80 | 0.84 | 0.82 | 0.86 | 0.84 | 0.90 |
-| Engineering | 0.70 | 0.64 | 0.70 | 0.76 | 0.74 | 0.72 | 0.80 | 0.80 |
-| Physics | 0.94 | 0.92 | 0.94 | 0.96 | 0.96 | 0.94 | 0.96 | 0.96 |
-| Chemistry | 0.86 | 0.88 | 0.90 | 0.90 | 0.94 | 0.92 | 0.90 | 0.94 |
-| **Average** | **0.852** | **0.836** | **0.835** | **0.865** | **0.872** | **0.876** | **0.868** | **0.888** |
-### Key Observations
-#### Quantization Level Impact
-- **3-bit**:
-  - g64/default: 85.2% average
-  - g128: 83.6% average (-1.6% vs g64/default)
-- **4-bit**:
-  - g64/default: 83.5% average
-  - g128: 86.5% average (+3.0% vs g64/default)
-- **6-bit**:
-  - g64/default: 87.2% average
-  - g128: 87.6% average (+0.4% vs g64/default)
-- **8-bit**:
-  - g64/default: 86.8% average
-  - g128: 88.8% average (+3.6% vs g64/default)
-#### Group Size Impact Across Quantization Levels
-| Quantization | g128 vs baseline | Performance Trend |
-|---|---|---|
-| 3-bit | -1.6% | g128 underperforms default |
-| 4-bit | +3.0% | g128 significantly outperforms default |
-| 6-bit | +0.4% | g128 slightly outperforms default |
-| 8-bit | +3.6% | g128 significantly outperforms default |
-### Important Disclaimer
-**The 3-bit g128 model shows a different performance pattern compared to higher bit quantizations:**
-- **3-bit**: g128 underperforms default (-1.6% difference)
-- **4-bit**: g128 outperforms default (+3.0% difference)
-- **6-bit**: g128 slightly outperforms default (+0.4% difference)
-- **8-bit**: g128 significantly outperforms default (+3.6% difference)
-This suggests that the group_size=128 optimization beneficial for 4-bit, 6-bit, and 8-bit quantizations does not translate to improved performance at the 3-bit level.
-## Usage
-```python
-import mlx_lm
-model_path = "petergilani/Qwen3-Coder-Next-3bit-g128"
-model, tokenizer = mlx_lm.load(model_path)
-prompt = "Write a Python function to calculate the factorial of a number."
-response = mlx_lm.generate(model, tokenizer, prompt=prompt)
-print(response)
-```
-## Conversion Details
-The model was converted using mlx_lm.convert with the following parameters:
-- q_bits=3
-- q_group_size=128
-- Quantization: 3-bit with main weights and fine-grained group_size 64 for MoE weights
-- Sampling parameters used for evaluation: temp=1.0, top_p=0.95, top_k=40
-## Evaluation Methodology
-- Tasks: MMLU Pro (math, computer science, engineering, physics, chemistry)
-- Questions per topic: 50
-- Evaluation framework: mlx_lm.evaluate
-- Sampling: temperature=1.0, top_p=0.95, top_k=40, num_shots=1
-## Model Details
-- **Base Model:** Qwen/Qwen3-Coder-Next
-- **Library:** mlx-lm
-- **Quantization:** 3-bit with group_size 128 for main weights and group_size 64 for MoE weights
-- **License:** apache-2.0
-- **Pipeline Tag:** text-generation
-- **Developed by:** petergilani
-- **Funded by [optional]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
-- **Model type:** [More Information Needed]
-- **Language(s) (NLP):** en
-- **License:** apache-2.0
-- **Finetuned from model [optional]:** Qwen/Qwen3-Coder-Next
-### Model Sources [optional]
-<!-- Provide the basic links for the model. -->
-- **Repository:** https://huggingface.co/petergilani/Qwen3-Coder-Next-3bit-g128
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
-## Uses
-<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
-### Direct Use
-<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
-[More Information Needed]
-### Downstream Use [optional]
-<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
-[More Information Needed]
-### Out-of-Scope Use
-<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
-[More Information Needed]
-## Bias, Risks, and Limitations
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
-[More Information Needed]
-### Recommendations
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
-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
-<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
-[More Information Needed]
-### Training Procedure
-<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
-#### Preprocessing [optional]
-[More Information Needed]
-#### Training Hyperparameters
-- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
-#### Speeds, Sizes, Times [optional]
-<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
-[More Information Needed]
-## Evaluation
-<!-- This section describes the evaluation protocols and provides the results. -->
-### Testing Data, Factors & Metrics
-#### Testing Data
-<!-- This should link to a Dataset Card if possible. -->
-[More Information Needed]
-#### Factors
-<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
-[More Information Needed]
-#### Metrics
-<!-- These are the evaluation metrics being used, ideally with a description of why. -->
-[More Information Needed]
-### Results
-[More Information Needed]
-#### Summary
-## Model Examination [optional]
-<!-- Relevant interpretability work for the model goes here -->
-[More Information Needed]
-## Environmental Impact
-<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
-Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
-- **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]
-<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
-**BibTeX:**
-[More Information Needed]
-**APA:**
-[More Information Needed]
-## Glossary [optional]
-<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
-[More Information Needed]
-## More Information [optional]
-[More Information Needed]
-## Model Card Authors [optional]
-[More Information Needed]
-## Model Card Contact
-[More Information Needed]

 ---
+library_name: mlx
 license: apache-2.0
+license_link: https://huggingface.co/Qwen/Qwen3-Coder-Next/blob/main/LICENSE
+pipeline_tag: text-generation
+base_model: Qwen/Qwen3-Coder-Next
 tags:
+- mlx
 ---