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README.md

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+---
+base_model: Felladrin/TinyMistral-248M-SFT-v4
+datasets:
+- OpenAssistant/oasst_top1_2023-08-25
+inference: false
+license: apache-2.0
+model_creator: Felladrin
+model_name: TinyMistral-248M-SFT-v4
+pipeline_tag: text-generation
+quantized_by: afrideva
+tags:
+- text-generation
+- gguf
+- ggml
+- quantized
+- q2_k
+- q3_k_m
+- q4_k_m
+- q5_k_m
+- q6_k
+- q8_0
+widget:
+- text: '<|im_start|>user
+
+    Invited some friends to come home today. Give me some ideas for games to play
+    with them!<|im_end|>
+
+    <|im_start|>assistant'
+- text: '<|im_start|>user
+
+    How do meteorologists predict how much air pollution will be produced in the next
+    year?<|im_end|>
+
+    <|im_start|>assistant'
+- text: '<|im_start|>user
+
+    Who is Mona Lisa?<|im_end|>
+
+    <|im_start|>assistant'
+- text: '<|im_start|>user
+
+    Heya!<|im_end|>
+
+    <|im_start|>assistant
+
+    Hi! How may I help you today?<|im_end|>
+
+    <|im_start|>user
+
+    I need to build a simple website. Where should I start learning about web development?<|im_end|>
+
+    <|im_start|>assistant'
+- text: '<|im_start|>user
+
+    What are some potential applications for quantum computing?<|im_end|>
+
+    <|im_start|>assistant'
+- text: '<|im_start|>user
+
+    Write the specs of a game about dragons and warriors in a fantasy world.<|im_end|>
+
+    <|im_start|>assistant'
+- text: "<|im_start|>user\nGot a question for you!<|im_end|>\n<|im_start|>assistant\nSure!
+    What's it?<|im_end|>\n<|im_start|>user\nWhy do you love cats so much!? \U0001F408<|im_end|>\n<|im_start|>assistant"
+- text: '<|im_start|>user
+
+    Tell me about the pros and cons of social media.<|im_end|>
+
+    <|im_start|>assistant'
+---
+# Felladrin/TinyMistral-248M-SFT-v4-GGUF
+
+Quantized GGUF model files for [TinyMistral-248M-SFT-v4](https://huggingface.co/Felladrin/TinyMistral-248M-SFT-v4) from [Felladrin](https://huggingface.co/Felladrin)
+
+
+| Name | Quant method | Size |
+| ---- | ---- | ---- |
+| [tinymistral-248m-sft-v4.fp16.gguf](https://huggingface.co/afrideva/TinyMistral-248M-SFT-v4-GGUF/resolve/main/tinymistral-248m-sft-v4.fp16.gguf) | fp16 | 497.75 MB  |
+| [tinymistral-248m-sft-v4.q2_k.gguf](https://huggingface.co/afrideva/TinyMistral-248M-SFT-v4-GGUF/resolve/main/tinymistral-248m-sft-v4.q2_k.gguf) | q2_k | 116.20 MB  |
+| [tinymistral-248m-sft-v4.q3_k_m.gguf](https://huggingface.co/afrideva/TinyMistral-248M-SFT-v4-GGUF/resolve/main/tinymistral-248m-sft-v4.q3_k_m.gguf) | q3_k_m | 131.01 MB  |
+| [tinymistral-248m-sft-v4.q4_k_m.gguf](https://huggingface.co/afrideva/TinyMistral-248M-SFT-v4-GGUF/resolve/main/tinymistral-248m-sft-v4.q4_k_m.gguf) | q4_k_m | 156.60 MB  |
+| [tinymistral-248m-sft-v4.q5_k_m.gguf](https://huggingface.co/afrideva/TinyMistral-248M-SFT-v4-GGUF/resolve/main/tinymistral-248m-sft-v4.q5_k_m.gguf) | q5_k_m | 180.16 MB  |
+| [tinymistral-248m-sft-v4.q6_k.gguf](https://huggingface.co/afrideva/TinyMistral-248M-SFT-v4-GGUF/resolve/main/tinymistral-248m-sft-v4.q6_k.gguf) | q6_k | 205.20 MB  |
+| [tinymistral-248m-sft-v4.q8_0.gguf](https://huggingface.co/afrideva/TinyMistral-248M-SFT-v4-GGUF/resolve/main/tinymistral-248m-sft-v4.q8_0.gguf) | q8_0 | 265.26 MB  |
+
+
+
+## Original Model Card:
+# Locutusque's TinyMistral-248M trained on OpenAssistant TOP-1 Conversation Threads
+
+- Base model: [Locutusque/TinyMistral-248M](https://huggingface.co/Locutusque/TinyMistral-248M)
+- Dataset: [OpenAssistant/oasst_top1_2023-08-25](https://huggingface.co/datasets/OpenAssistant/oasst_top1_2023-08-25)
+- Availability in other ML formats:
+  - GGUF: [Felladrin/gguf-TinyMistral-248M-SFT-v4](https://huggingface.co/Felladrin/gguf-TinyMistral-248M-SFT-v4)
+  - ONNX: [Felladrin/onnx-TinyMistral-248M-SFT-v4](https://huggingface.co/Felladrin/onnx-TinyMistral-248M-SFT-v4)
+
+## Recommended Prompt Format
+
+```
+<|im_start|>user
+{message}<|im_end|>
+<|im_start|>assistant
+```