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Model: hoangton/gemma-2b-GGUF Source: Original Platform
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---
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library_name: transformers
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tags: []
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extra_gated_heading: "Access Gemma on Hugging Face"
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extra_gated_prompt: "To access Gemma on Hugging Face, you’re required to review and agree to Google’s usage license. To do this, please ensure you’re logged-in to Hugging Face and click below. Requests are processed immediately."
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extra_gated_button_content: "Acknowledge license"
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license: other
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license_name: gemma-terms-of-use
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license_link: https://ai.google.dev/gemma/terms
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---
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# Gemma-2B GGUF
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This is a quantized version of the [google/gemma-2b](https://huggingface.co/google/gemma-2b) model using [llama.cpp](https://github.com/ggerganov/llama.cpp).
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This model card corresponds to the 2B base version of the Gemma model. You can also visit the model card of the [7B base model](https://huggingface.co/google/gemma-7b), [7B instruct model](https://huggingface.co/google/gemma-7b-it), and [2B instruct model](https://huggingface.co/google/gemma-2b-it).
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**Model Page**: [Gemma](https://ai.google.dev/gemma/docs)
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**Terms of Use**: [Terms](https://www.kaggle.com/models/google/gemma/license/consent)
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## ⚡ Quants
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* `q2_k`: Uses Q4_K for the attention.vw and feed_forward.w2 tensors, Q2_K for the other tensors.
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* `q3_k_l`: Uses Q5_K for the attention.wv, attention.wo, and feed_forward.w2 tensors, else Q3_K
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* `q3_k_m`: Uses Q4_K for the attention.wv, attention.wo, and feed_forward.w2 tensors, else Q3_K
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* `q3_k_s`: Uses Q3_K for all tensors
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* `q4_0`: Original quant method, 4-bit.
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* `q4_1`: Higher accuracy than q4_0 but not as high as q5_0. However has quicker inference than q5 models.
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* `q4_k_m`: Uses Q6_K for half of the attention.wv and feed_forward.w2 tensors, else Q4_K
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* `q4_k_s`: Uses Q4_K for all tensors
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* `q5_0`: Higher accuracy, higher resource usage and slower inference.
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* `q5_1`: Even higher accuracy, resource usage and slower inference.
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* `q5_k_m`: Uses Q6_K for half of the attention.wv and feed_forward.w2 tensors, else Q5_K
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* `q5_k_s`: Uses Q5_K for all tensors
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* `q6_k`: Uses Q8_K for all tensors
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* `q8_0`: Almost indistinguishable from float16. High resource use and slow. Not recommended for most users.
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## 💻 Usage
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This model can be used with the latest version of llama.cpp and LM Studio >0.2.16.
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