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README.md

@@ -1,16 +1,14 @@
 ---
-language:
-- en
 library_name: transformers
-license: apache-2.0
 tags:
-- unsloth
-- transformers
-- gemma
-- gemma-2b
 - TensorBlock
 - GGUF
-base_model: unsloth/gemma-2b
+extra_gated_heading: Access Gemma on Hugging Face
+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.
+extra_gated_button_content: Acknowledge license
+base_model: 4bit/gemma-2b
 ---
 
 <div style="width: auto; margin-left: auto; margin-right: auto">
@@ -24,13 +22,12 @@ base_model: unsloth/gemma-2b
     </div>
 </div>
 
-## unsloth/gemma-2b - GGUF
+## 4bit/gemma-2b - GGUF
 
-This repo contains GGUF format model files for [unsloth/gemma-2b](https://huggingface.co/unsloth/gemma-2b).
+This repo contains GGUF format model files for [4bit/gemma-2b](https://huggingface.co/4bit/gemma-2b).
 
 The files were quantized using machines provided by [TensorBlock](https://tensorblock.co/), and they are compatible with llama.cpp as of [commit b4011](https://github.com/ggerganov/llama.cpp/commit/a6744e43e80f4be6398fc7733a01642c846dce1d).
 
-
 <div style="text-align: left; margin: 20px 0;">
     <a href="https://tensorblock.co/waitlist/client" style="display: inline-block; padding: 10px 20px; background-color: #007bff; color: white; text-decoration: none; border-radius: 5px; font-weight: bold;">
         Run them on the TensorBlock client using your local machine ↗
@@ -39,7 +36,6 @@ The files were quantized using machines provided by [TensorBlock](https://tensor
 
 ## Prompt template
 
-
 ```
 
 ```
@@ -48,18 +44,18 @@ The files were quantized using machines provided by [TensorBlock](https://tensor
 
 | Filename | Quant type | File Size | Description |
 | -------- | ---------- | --------- | ----------- |
-| [gemma-2b-Q2_K.gguf](https://huggingface.co/tensorblock/gemma-2b-GGUF/blob/main/gemma-2b-Q2_K.gguf) | Q2_K | 1.078 GB | smallest, significant quality loss - not recommended for most purposes |
-| [gemma-2b-Q3_K_S.gguf](https://huggingface.co/tensorblock/gemma-2b-GGUF/blob/main/gemma-2b-Q3_K_S.gguf) | Q3_K_S | 1.200 GB | very small, high quality loss |
-| [gemma-2b-Q3_K_M.gguf](https://huggingface.co/tensorblock/gemma-2b-GGUF/blob/main/gemma-2b-Q3_K_M.gguf) | Q3_K_M | 1.289 GB | very small, high quality loss |
-| [gemma-2b-Q3_K_L.gguf](https://huggingface.co/tensorblock/gemma-2b-GGUF/blob/main/gemma-2b-Q3_K_L.gguf) | Q3_K_L | 1.365 GB | small, substantial quality loss |
-| [gemma-2b-Q4_0.gguf](https://huggingface.co/tensorblock/gemma-2b-GGUF/blob/main/gemma-2b-Q4_0.gguf) | Q4_0 | 1.445 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
-| [gemma-2b-Q4_K_S.gguf](https://huggingface.co/tensorblock/gemma-2b-GGUF/blob/main/gemma-2b-Q4_K_S.gguf) | Q4_K_S | 1.453 GB | small, greater quality loss |
-| [gemma-2b-Q4_K_M.gguf](https://huggingface.co/tensorblock/gemma-2b-GGUF/blob/main/gemma-2b-Q4_K_M.gguf) | Q4_K_M | 1.518 GB | medium, balanced quality - recommended |
-| [gemma-2b-Q5_0.gguf](https://huggingface.co/tensorblock/gemma-2b-GGUF/blob/main/gemma-2b-Q5_0.gguf) | Q5_0 | 1.675 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
-| [gemma-2b-Q5_K_S.gguf](https://huggingface.co/tensorblock/gemma-2b-GGUF/blob/main/gemma-2b-Q5_K_S.gguf) | Q5_K_S | 1.675 GB | large, low quality loss - recommended |
-| [gemma-2b-Q5_K_M.gguf](https://huggingface.co/tensorblock/gemma-2b-GGUF/blob/main/gemma-2b-Q5_K_M.gguf) | Q5_K_M | 1.713 GB | large, very low quality loss - recommended |
-| [gemma-2b-Q6_K.gguf](https://huggingface.co/tensorblock/gemma-2b-GGUF/blob/main/gemma-2b-Q6_K.gguf) | Q6_K | 1.921 GB | very large, extremely low quality loss |
-| [gemma-2b-Q8_0.gguf](https://huggingface.co/tensorblock/gemma-2b-GGUF/blob/main/gemma-2b-Q8_0.gguf) | Q8_0 | 2.486 GB | very large, extremely low quality loss - not recommended |
+| [gemma-2b-Q2_K.gguf](https://huggingface.co/tensorblock/gemma-2b-GGUF/blob/main/gemma-2b-Q2_K.gguf) | Q2_K | 1.158 GB | smallest, significant quality loss - not recommended for most purposes |
+| [gemma-2b-Q3_K_S.gguf](https://huggingface.co/tensorblock/gemma-2b-GGUF/blob/main/gemma-2b-Q3_K_S.gguf) | Q3_K_S | 1.288 GB | very small, high quality loss |
+| [gemma-2b-Q3_K_M.gguf](https://huggingface.co/tensorblock/gemma-2b-GGUF/blob/main/gemma-2b-Q3_K_M.gguf) | Q3_K_M | 1.384 GB | very small, high quality loss |
+| [gemma-2b-Q3_K_L.gguf](https://huggingface.co/tensorblock/gemma-2b-GGUF/blob/main/gemma-2b-Q3_K_L.gguf) | Q3_K_L | 1.466 GB | small, substantial quality loss |
+| [gemma-2b-Q4_0.gguf](https://huggingface.co/tensorblock/gemma-2b-GGUF/blob/main/gemma-2b-Q4_0.gguf) | Q4_0 | 1.551 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
+| [gemma-2b-Q4_K_S.gguf](https://huggingface.co/tensorblock/gemma-2b-GGUF/blob/main/gemma-2b-Q4_K_S.gguf) | Q4_K_S | 1.560 GB | small, greater quality loss |
+| [gemma-2b-Q4_K_M.gguf](https://huggingface.co/tensorblock/gemma-2b-GGUF/blob/main/gemma-2b-Q4_K_M.gguf) | Q4_K_M | 1.630 GB | medium, balanced quality - recommended |
+| [gemma-2b-Q5_0.gguf](https://huggingface.co/tensorblock/gemma-2b-GGUF/blob/main/gemma-2b-Q5_0.gguf) | Q5_0 | 1.799 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
+| [gemma-2b-Q5_K_S.gguf](https://huggingface.co/tensorblock/gemma-2b-GGUF/blob/main/gemma-2b-Q5_K_S.gguf) | Q5_K_S | 1.799 GB | large, low quality loss - recommended |
+| [gemma-2b-Q5_K_M.gguf](https://huggingface.co/tensorblock/gemma-2b-GGUF/blob/main/gemma-2b-Q5_K_M.gguf) | Q5_K_M | 1.840 GB | large, very low quality loss - recommended |
+| [gemma-2b-Q6_K.gguf](https://huggingface.co/tensorblock/gemma-2b-GGUF/blob/main/gemma-2b-Q6_K.gguf) | Q6_K | 2.062 GB | very large, extremely low quality loss |
+| [gemma-2b-Q8_0.gguf](https://huggingface.co/tensorblock/gemma-2b-GGUF/blob/main/gemma-2b-Q8_0.gguf) | Q8_0 | 2.669 GB | very large, extremely low quality loss - not recommended |
 
 
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