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