Upload folder using huggingface_hub

Mistral-7B-v0.1-Q2_K.gguf

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Mistral-7B-v0.1-Q3_K_L.gguf

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Mistral-7B-v0.1-Q5_0.gguf

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Mistral-7B-v0.1-Q5_K_S.gguf

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Mistral-7B-v0.1-Q8_0.gguf

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README.md

@@ -1,8 +1,18 @@
 ---
-base_model: wons/mistral-7B-v0.1
+language:
+- en
+license: apache-2.0
 tags:
+- pretrained
 - TensorBlock
 - GGUF
+pipeline_tag: text-generation
+inference:
+  parameters:
+    temperature: 0.7
+extra_gated_description: If you want to learn more about how we process your personal
+  data, please read our <a href="https://mistral.ai/terms/">Privacy Policy</a>.
+base_model: mistralai/Mistral-7B-v0.1
 ---
 
 <div style="width: auto; margin-left: auto; margin-right: auto">
@@ -16,13 +26,12 @@ tags:
     </div>
 </div>
 
-## wons/mistral-7B-v0.1 - GGUF
+## mistralai/Mistral-7B-v0.1 - GGUF
 
-This repo contains GGUF format model files for [wons/mistral-7B-v0.1](https://huggingface.co/wons/mistral-7B-v0.1).
+This repo contains GGUF format model files for [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1).
 
 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 ↗
@@ -31,7 +40,6 @@ The files were quantized using machines provided by [TensorBlock](https://tensor
 
 ## Prompt template
 
-
 ```
 
 ```
@@ -40,18 +48,18 @@ The files were quantized using machines provided by [TensorBlock](https://tensor
 
 | Filename | Quant type | File Size | Description |
 | -------- | ---------- | --------- | ----------- |
-| [mistral-7B-v0.1-Q2_K.gguf](https://huggingface.co/tensorblock/mistral-7B-v0.1-GGUF/blob/main/mistral-7B-v0.1-Q2_K.gguf) | Q2_K | 2.532 GB | smallest, significant quality loss - not recommended for most purposes |
-| [mistral-7B-v0.1-Q3_K_S.gguf](https://huggingface.co/tensorblock/mistral-7B-v0.1-GGUF/blob/main/mistral-7B-v0.1-Q3_K_S.gguf) | Q3_K_S | 2.947 GB | very small, high quality loss |
-| [mistral-7B-v0.1-Q3_K_M.gguf](https://huggingface.co/tensorblock/mistral-7B-v0.1-GGUF/blob/main/mistral-7B-v0.1-Q3_K_M.gguf) | Q3_K_M | 3.277 GB | very small, high quality loss |
-| [mistral-7B-v0.1-Q3_K_L.gguf](https://huggingface.co/tensorblock/mistral-7B-v0.1-GGUF/blob/main/mistral-7B-v0.1-Q3_K_L.gguf) | Q3_K_L | 3.560 GB | small, substantial quality loss |
-| [mistral-7B-v0.1-Q4_0.gguf](https://huggingface.co/tensorblock/mistral-7B-v0.1-GGUF/blob/main/mistral-7B-v0.1-Q4_0.gguf) | Q4_0 | 3.827 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
-| [mistral-7B-v0.1-Q4_K_S.gguf](https://huggingface.co/tensorblock/mistral-7B-v0.1-GGUF/blob/main/mistral-7B-v0.1-Q4_K_S.gguf) | Q4_K_S | 3.856 GB | small, greater quality loss |
-| [mistral-7B-v0.1-Q4_K_M.gguf](https://huggingface.co/tensorblock/mistral-7B-v0.1-GGUF/blob/main/mistral-7B-v0.1-Q4_K_M.gguf) | Q4_K_M | 4.068 GB | medium, balanced quality - recommended |
-| [mistral-7B-v0.1-Q5_0.gguf](https://huggingface.co/tensorblock/mistral-7B-v0.1-GGUF/blob/main/mistral-7B-v0.1-Q5_0.gguf) | Q5_0 | 4.654 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
-| [mistral-7B-v0.1-Q5_K_S.gguf](https://huggingface.co/tensorblock/mistral-7B-v0.1-GGUF/blob/main/mistral-7B-v0.1-Q5_K_S.gguf) | Q5_K_S | 4.654 GB | large, low quality loss - recommended |
-| [mistral-7B-v0.1-Q5_K_M.gguf](https://huggingface.co/tensorblock/mistral-7B-v0.1-GGUF/blob/main/mistral-7B-v0.1-Q5_K_M.gguf) | Q5_K_M | 4.779 GB | large, very low quality loss - recommended |
-| [mistral-7B-v0.1-Q6_K.gguf](https://huggingface.co/tensorblock/mistral-7B-v0.1-GGUF/blob/main/mistral-7B-v0.1-Q6_K.gguf) | Q6_K | 5.534 GB | very large, extremely low quality loss |
-| [mistral-7B-v0.1-Q8_0.gguf](https://huggingface.co/tensorblock/mistral-7B-v0.1-GGUF/blob/main/mistral-7B-v0.1-Q8_0.gguf) | Q8_0 | 7.167 GB | very large, extremely low quality loss - not recommended |
+| [Mistral-7B-v0.1-Q2_K.gguf](https://huggingface.co/tensorblock/Mistral-7B-v0.1-GGUF/blob/main/Mistral-7B-v0.1-Q2_K.gguf) | Q2_K | 2.719 GB | smallest, significant quality loss - not recommended for most purposes |
+| [Mistral-7B-v0.1-Q3_K_S.gguf](https://huggingface.co/tensorblock/Mistral-7B-v0.1-GGUF/blob/main/Mistral-7B-v0.1-Q3_K_S.gguf) | Q3_K_S | 3.165 GB | very small, high quality loss |
+| [Mistral-7B-v0.1-Q3_K_M.gguf](https://huggingface.co/tensorblock/Mistral-7B-v0.1-GGUF/blob/main/Mistral-7B-v0.1-Q3_K_M.gguf) | Q3_K_M | 3.519 GB | very small, high quality loss |
+| [Mistral-7B-v0.1-Q3_K_L.gguf](https://huggingface.co/tensorblock/Mistral-7B-v0.1-GGUF/blob/main/Mistral-7B-v0.1-Q3_K_L.gguf) | Q3_K_L | 3.822 GB | small, substantial quality loss |
+| [Mistral-7B-v0.1-Q4_0.gguf](https://huggingface.co/tensorblock/Mistral-7B-v0.1-GGUF/blob/main/Mistral-7B-v0.1-Q4_0.gguf) | Q4_0 | 4.109 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
+| [Mistral-7B-v0.1-Q4_K_S.gguf](https://huggingface.co/tensorblock/Mistral-7B-v0.1-GGUF/blob/main/Mistral-7B-v0.1-Q4_K_S.gguf) | Q4_K_S | 4.140 GB | small, greater quality loss |
+| [Mistral-7B-v0.1-Q4_K_M.gguf](https://huggingface.co/tensorblock/Mistral-7B-v0.1-GGUF/blob/main/Mistral-7B-v0.1-Q4_K_M.gguf) | Q4_K_M | 4.368 GB | medium, balanced quality - recommended |
+| [Mistral-7B-v0.1-Q5_0.gguf](https://huggingface.co/tensorblock/Mistral-7B-v0.1-GGUF/blob/main/Mistral-7B-v0.1-Q5_0.gguf) | Q5_0 | 4.998 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
+| [Mistral-7B-v0.1-Q5_K_S.gguf](https://huggingface.co/tensorblock/Mistral-7B-v0.1-GGUF/blob/main/Mistral-7B-v0.1-Q5_K_S.gguf) | Q5_K_S | 4.998 GB | large, low quality loss - recommended |
+| [Mistral-7B-v0.1-Q5_K_M.gguf](https://huggingface.co/tensorblock/Mistral-7B-v0.1-GGUF/blob/main/Mistral-7B-v0.1-Q5_K_M.gguf) | Q5_K_M | 5.131 GB | large, very low quality loss - recommended |
+| [Mistral-7B-v0.1-Q6_K.gguf](https://huggingface.co/tensorblock/Mistral-7B-v0.1-GGUF/blob/main/Mistral-7B-v0.1-Q6_K.gguf) | Q6_K | 5.942 GB | very large, extremely low quality loss |
+| [Mistral-7B-v0.1-Q8_0.gguf](https://huggingface.co/tensorblock/Mistral-7B-v0.1-GGUF/blob/main/Mistral-7B-v0.1-Q8_0.gguf) | Q8_0 | 7.696 GB | very large, extremely low quality loss - not recommended |
 
 
 ## Downloading instruction
@@ -67,11 +75,11 @@ pip install -U "huggingface_hub[cli]"
 Then, downoad the individual model file the a local directory
 
 ```shell
-huggingface-cli download tensorblock/mistral-7B-v0.1-GGUF --include "mistral-7B-v0.1-Q2_K.gguf" --local-dir MY_LOCAL_DIR
+huggingface-cli download tensorblock/Mistral-7B-v0.1-GGUF --include "Mistral-7B-v0.1-Q2_K.gguf" --local-dir MY_LOCAL_DIR
 ```
 
 If you wanna download multiple model files with a pattern (e.g., `*Q4_K*gguf`), you can try:
 
 ```shell
-huggingface-cli download tensorblock/mistral-7B-v0.1-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
+huggingface-cli download tensorblock/Mistral-7B-v0.1-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
 ```