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README.md
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---
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base_model: Dimensity/Dimensity-3B
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inference: false
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language:
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- en
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license: mit
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model_creator: Dimensity
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model_name: Dimensity-3B
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pipeline_tag: text-generation
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quantized_by: afrideva
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tags:
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- sft
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- gguf
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- ggml
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- quantized
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- q2_k
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- q3_k_m
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- q4_k_m
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- q5_k_m
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- q6_k
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- q8_0
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---
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# Dimensity/Dimensity-3B-GGUF
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Quantized GGUF model files for [Dimensity-3B](https://huggingface.co/Dimensity/Dimensity-3B) from [Dimensity](https://huggingface.co/Dimensity)
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| Name | Quant method | Size |
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| ---- | ---- | ---- |
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| [dimensity-3b.fp16.gguf](https://huggingface.co/afrideva/Dimensity-3B-GGUF/resolve/main/dimensity-3b.fp16.gguf) | fp16 | 5.59 GB |
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| [dimensity-3b.q2_k.gguf](https://huggingface.co/afrideva/Dimensity-3B-GGUF/resolve/main/dimensity-3b.q2_k.gguf) | q2_k | 1.20 GB |
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| [dimensity-3b.q3_k_m.gguf](https://huggingface.co/afrideva/Dimensity-3B-GGUF/resolve/main/dimensity-3b.q3_k_m.gguf) | q3_k_m | 1.39 GB |
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| [dimensity-3b.q4_k_m.gguf](https://huggingface.co/afrideva/Dimensity-3B-GGUF/resolve/main/dimensity-3b.q4_k_m.gguf) | q4_k_m | 1.71 GB |
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| [dimensity-3b.q5_k_m.gguf](https://huggingface.co/afrideva/Dimensity-3B-GGUF/resolve/main/dimensity-3b.q5_k_m.gguf) | q5_k_m | 1.99 GB |
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| [dimensity-3b.q6_k.gguf](https://huggingface.co/afrideva/Dimensity-3B-GGUF/resolve/main/dimensity-3b.q6_k.gguf) | q6_k | 2.30 GB |
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| [dimensity-3b.q8_0.gguf](https://huggingface.co/afrideva/Dimensity-3B-GGUF/resolve/main/dimensity-3b.q8_0.gguf) | q8_0 | 2.97 GB |
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## Original Model Card:
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```Dimensity-3B```
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# Model Details
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Dimensity-3B is a finetuned version of the StableLM framework trained on a variety of conversational data. It contains 3 billion parameters.
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# Intended Uses
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This model is intended for conversational AI applications. It can engage in open-ended dialogue by generating responses to user prompts.
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## Factors
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# Training Data
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The model was trained on a large dataset of over 100 million conversational exchanges extracted from Reddit comments, customer support logs, and other online dialogues.
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# Prompt Template
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The model was finetuned using the following prompt template:
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```
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### Human: {prompt}
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### Assistant:
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```
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This prompts the model to take on an assistant role.
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# Ethical Considerations
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As the model was trained on public conversational data, it may generate responses that contain harmful stereotypes or toxic content. The model should be used with caution in sensitive contexts.
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# Caveats and Recommendations
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This model is designed for open-ended conversation. It may sometimes generate plausible-sounding but incorrect information. Outputs should be validated against external sources.
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