Model Card for Model ID
This modelcard aims to be a base template for new models. It has been generated using this raw template.
Model Details
⚠️ Important Technical Note
This model is based on weights that have already been quantized to 4-bit during the optimization process (via heretic-llm). It was then converted to the GGUF format.
Source: 4-bit quantized weights.
Quality: The effective quality corresponds to that of a 4-bit model at most, even if the GGUF quantization (e.g., Q8_0 or fp16) suggests higher precision.
Model Description
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- Language(s) (NLP): [More Information Needed]
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- Finetuned from model [optional]: [More Information Needed]
Model Sources [optional]
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Uses
Direct Use
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Downstream Use [optional]
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Out-of-Scope Use
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Bias, Risks, and Limitations
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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.
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Training Details
Training Data
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Training Procedure
Preprocessing [optional]
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Training Hyperparameters
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Speeds, Sizes, Times [optional]
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Evaluation
Testing Data, Factors & Metrics
Testing Data
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Factors
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Metrics
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Results
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Summary
Model Examination [optional]
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Environmental Impact
Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).
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- Hours used: [More Information Needed]
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- Carbon Emitted: [More Information Needed]
Technical Specifications [optional]
Model Architecture and Objective
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Compute Infrastructure
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Hardware
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Software
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Citation [optional]
BibTeX:
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APA:
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Glossary [optional]
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Model Card Authors [optional]
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Model Card Contact
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