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README.md
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- **Model type:** Language Model (Causal LM)
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- **Finetuned from model:** Mistral-7B
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### Model Sources
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- **Repository:** [Hugging Face Model Repository](https://huggingface.co/Hend-10/MistralActia)
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This model can be used directly for generating code snippets, examples, and explanations in C programming. It is useful for developers, educators, and researchers who need assistance with C code generation.
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### Downstream Use
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The model can be integrated into applications and tools that assist with coding tasks, such as IDE plugins, coding assistants, and educational platforms for programming.
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The model performs well on a range of C programming tasks, though further fine-tuning and evaluation on more diverse datasets could enhance its robustness and applicability.
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## Model Examination
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The model's interpretability is an ongoing area of research. Examination of model outputs includes analyzing the consistency and relevance of generated code snippets relative to the provided prompts.
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## Environmental Impact
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## Technical Specifications
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### Model Architecture and Objective
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- **Libraries:** Datasets, Accelerate, PEFT, TRL
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## Citation
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**BibTeX:**
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```bibtex
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- **Model type:** Language Model (Causal LM)
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- **Finetuned from model:** Mistral-7B
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### Model Sources
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- **Repository:** [Hugging Face Model Repository](https://huggingface.co/Hend-10/MistralActia)
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|
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|
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This model can be used directly for generating code snippets, examples, and explanations in C programming. It is useful for developers, educators, and researchers who need assistance with C code generation.
|
| 31 |
|
| 32 |
|
| 33 |
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### Downstream Use
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| 34 |
|
| 35 |
The model can be integrated into applications and tools that assist with coding tasks, such as IDE plugins, coding assistants, and educational platforms for programming.
|
| 36 |
|
|
|
|
| 143 |
The model performs well on a range of C programming tasks, though further fine-tuning and evaluation on more diverse datasets could enhance its robustness and applicability.
|
| 144 |
|
| 145 |
|
| 146 |
+
## Model Examination
|
| 147 |
|
| 148 |
The model's interpretability is an ongoing area of research. Examination of model outputs includes analyzing the consistency and relevance of generated code snippets relative to the provided prompts.
|
| 149 |
## Environmental Impact
|
| 150 |
+
## Technical Specifications
|
| 151 |
|
| 152 |
### Model Architecture and Objective
|
| 153 |
|
|
|
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| 168 |
- **Libraries:** Datasets, Accelerate, PEFT, TRL
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## Citation
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**BibTeX:**
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```bibtex
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