GGUF
Mixture of Experts
frankenmoe
Merge
mergekit
lazymergekit
Locutusque/TinyMistral-248M-v2
Locutusque/TinyMistral-248M-v2.5
Locutusque/TinyMistral-248M-v2.5-Instruct
jtatman/tinymistral-v2-pycoder-instruct-248m
Felladrin/TinyMistral-248M-SFT-v4
Locutusque/TinyMistral-248M-v2-Instruct
TensorBlock
GGUF
Inference Endpoints
Upload folder using huggingface_hub
Browse files- .gitattributes +12 -0
- README.md +108 -0
- TinyMistral-6x248M-Q2_K.gguf +3 -0
- TinyMistral-6x248M-Q3_K_L.gguf +3 -0
- TinyMistral-6x248M-Q3_K_M.gguf +3 -0
- TinyMistral-6x248M-Q3_K_S.gguf +3 -0
- TinyMistral-6x248M-Q4_0.gguf +3 -0
- TinyMistral-6x248M-Q4_K_M.gguf +3 -0
- TinyMistral-6x248M-Q4_K_S.gguf +3 -0
- TinyMistral-6x248M-Q5_0.gguf +3 -0
- TinyMistral-6x248M-Q5_K_M.gguf +3 -0
- TinyMistral-6x248M-Q5_K_S.gguf +3 -0
- TinyMistral-6x248M-Q6_K.gguf +3 -0
- TinyMistral-6x248M-Q8_0.gguf +3 -0
.gitattributes
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@@ -33,3 +33,15 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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TinyMistral-6x248M-Q2_K.gguf filter=lfs diff=lfs merge=lfs -text
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TinyMistral-6x248M-Q3_K_L.gguf filter=lfs diff=lfs merge=lfs -text
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TinyMistral-6x248M-Q3_K_M.gguf filter=lfs diff=lfs merge=lfs -text
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TinyMistral-6x248M-Q3_K_S.gguf filter=lfs diff=lfs merge=lfs -text
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TinyMistral-6x248M-Q4_0.gguf filter=lfs diff=lfs merge=lfs -text
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TinyMistral-6x248M-Q4_K_M.gguf filter=lfs diff=lfs merge=lfs -text
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TinyMistral-6x248M-Q4_K_S.gguf filter=lfs diff=lfs merge=lfs -text
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TinyMistral-6x248M-Q5_0.gguf filter=lfs diff=lfs merge=lfs -text
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TinyMistral-6x248M-Q5_K_M.gguf filter=lfs diff=lfs merge=lfs -text
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TinyMistral-6x248M-Q5_K_S.gguf filter=lfs diff=lfs merge=lfs -text
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TinyMistral-6x248M-Q6_K.gguf filter=lfs diff=lfs merge=lfs -text
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TinyMistral-6x248M-Q8_0.gguf filter=lfs diff=lfs merge=lfs -text
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README.md
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1 |
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---
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license: apache-2.0
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tags:
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- moe
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- frankenmoe
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- merge
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- mergekit
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- lazymergekit
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- Locutusque/TinyMistral-248M-v2
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- Locutusque/TinyMistral-248M-v2.5
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- Locutusque/TinyMistral-248M-v2.5-Instruct
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- jtatman/tinymistral-v2-pycoder-instruct-248m
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- Felladrin/TinyMistral-248M-SFT-v4
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- Locutusque/TinyMistral-248M-v2-Instruct
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- TensorBlock
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- GGUF
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base_model: M4-ai/TinyMistral-6x248M
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inference:
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parameters:
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do_sample: true
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temperature: 0.2
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top_p: 0.14
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top_k: 12
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max_new_tokens: 250
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repetition_penalty: 1.15
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widget:
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- text: '<|im_start|>user
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Write me a Python program that calculates the factorial of n. <|im_end|>
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<|im_start|>assistant
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'
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- text: An emerging clinical approach to treat substance abuse disorders involves
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a form of cognitive-behavioral therapy whereby addicts learn to reduce their reactivity
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to drug-paired stimuli through cue-exposure or extinction training. It is, however,
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datasets:
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- nampdn-ai/mini-peS2o
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---
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<div style="width: auto; margin-left: auto; margin-right: auto">
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<img src="https://i.imgur.com/jC7kdl8.jpeg" alt="TensorBlock" style="width: 100%; min-width: 400px; display: block; margin: auto;">
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</div>
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<div style="display: flex; justify-content: space-between; width: 100%;">
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<div style="display: flex; flex-direction: column; align-items: flex-start;">
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<p style="margin-top: 0.5em; margin-bottom: 0em;">
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Feedback and support: TensorBlock's <a href="https://x.com/tensorblock_aoi">Twitter/X</a>, <a href="https://t.me/TensorBlock">Telegram Group</a> and <a href="https://x.com/tensorblock_aoi">Discord server</a>
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</p>
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</div>
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</div>
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## M4-ai/TinyMistral-6x248M - GGUF
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This repo contains GGUF format model files for [M4-ai/TinyMistral-6x248M](https://huggingface.co/M4-ai/TinyMistral-6x248M).
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The files were quantized using machines provided by [TensorBlock](https://tensorblock.co/), and they are compatible with llama.cpp as of [commit b4242](https://github.com/ggerganov/llama.cpp/commit/a6744e43e80f4be6398fc7733a01642c846dce1d).
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<div style="text-align: left; margin: 20px 0;">
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<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;">
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Run them on the TensorBlock client using your local machine ↗
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</a>
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</div>
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## Prompt template
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```
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```
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## Model file specification
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| Filename | Quant type | File Size | Description |
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| -------- | ---------- | --------- | ----------- |
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| [TinyMistral-6x248M-Q2_K.gguf](https://huggingface.co/tensorblock/TinyMistral-6x248M-GGUF/blob/main/TinyMistral-6x248M-Q2_K.gguf) | Q2_K | 0.379 GB | smallest, significant quality loss - not recommended for most purposes |
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| [TinyMistral-6x248M-Q3_K_S.gguf](https://huggingface.co/tensorblock/TinyMistral-6x248M-GGUF/blob/main/TinyMistral-6x248M-Q3_K_S.gguf) | Q3_K_S | 0.445 GB | very small, high quality loss |
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| [TinyMistral-6x248M-Q3_K_M.gguf](https://huggingface.co/tensorblock/TinyMistral-6x248M-GGUF/blob/main/TinyMistral-6x248M-Q3_K_M.gguf) | Q3_K_M | 0.487 GB | very small, high quality loss |
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| [TinyMistral-6x248M-Q3_K_L.gguf](https://huggingface.co/tensorblock/TinyMistral-6x248M-GGUF/blob/main/TinyMistral-6x248M-Q3_K_L.gguf) | Q3_K_L | 0.527 GB | small, substantial quality loss |
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| [TinyMistral-6x248M-Q4_0.gguf](https://huggingface.co/tensorblock/TinyMistral-6x248M-GGUF/blob/main/TinyMistral-6x248M-Q4_0.gguf) | Q4_0 | 0.574 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
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| [TinyMistral-6x248M-Q4_K_S.gguf](https://huggingface.co/tensorblock/TinyMistral-6x248M-GGUF/blob/main/TinyMistral-6x248M-Q4_K_S.gguf) | Q4_K_S | 0.577 GB | small, greater quality loss |
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| [TinyMistral-6x248M-Q4_K_M.gguf](https://huggingface.co/tensorblock/TinyMistral-6x248M-GGUF/blob/main/TinyMistral-6x248M-Q4_K_M.gguf) | Q4_K_M | 0.613 GB | medium, balanced quality - recommended |
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| [TinyMistral-6x248M-Q5_0.gguf](https://huggingface.co/tensorblock/TinyMistral-6x248M-GGUF/blob/main/TinyMistral-6x248M-Q5_0.gguf) | Q5_0 | 0.695 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
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| [TinyMistral-6x248M-Q5_K_S.gguf](https://huggingface.co/tensorblock/TinyMistral-6x248M-GGUF/blob/main/TinyMistral-6x248M-Q5_K_S.gguf) | Q5_K_S | 0.695 GB | large, low quality loss - recommended |
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| [TinyMistral-6x248M-Q5_K_M.gguf](https://huggingface.co/tensorblock/TinyMistral-6x248M-GGUF/blob/main/TinyMistral-6x248M-Q5_K_M.gguf) | Q5_K_M | 0.715 GB | large, very low quality loss - recommended |
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| [TinyMistral-6x248M-Q6_K.gguf](https://huggingface.co/tensorblock/TinyMistral-6x248M-GGUF/blob/main/TinyMistral-6x248M-Q6_K.gguf) | Q6_K | 0.824 GB | very large, extremely low quality loss |
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| [TinyMistral-6x248M-Q8_0.gguf](https://huggingface.co/tensorblock/TinyMistral-6x248M-GGUF/blob/main/TinyMistral-6x248M-Q8_0.gguf) | Q8_0 | 1.067 GB | very large, extremely low quality loss - not recommended |
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## Downloading instruction
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### Command line
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Firstly, install Huggingface Client
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```shell
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pip install -U "huggingface_hub[cli]"
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```
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Then, downoad the individual model file the a local directory
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```shell
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huggingface-cli download tensorblock/TinyMistral-6x248M-GGUF --include "TinyMistral-6x248M-Q2_K.gguf" --local-dir MY_LOCAL_DIR
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```
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If you wanna download multiple model files with a pattern (e.g., `*Q4_K*gguf`), you can try:
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```shell
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huggingface-cli download tensorblock/TinyMistral-6x248M-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
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```
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TinyMistral-6x248M-Q2_K.gguf
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TinyMistral-6x248M-Q3_K_L.gguf
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