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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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+
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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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+
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+
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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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+
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+
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+
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+ ## Original Model Card:
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+ ```Dimensity-3B```
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+
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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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+
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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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+
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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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+
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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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+
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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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+
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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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+
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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.