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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
``` |