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README.md
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---
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base_model: simplescaling/s1.1-7B
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library_name: transformers
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model_name: Qwen2.5-14B-Instruct-20250308_215306
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tags:
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- generated_from_trainer
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- trl
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- sft
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- TensorBlock
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- GGUF
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licence: license
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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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## simplescaling/s1.1-7B - GGUF
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This repo contains GGUF format model files for [simplescaling/s1.1-7B](https://huggingface.co/simplescaling/s1.1-7B).
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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 b4882](https://github.com/ggml-org/llama.cpp/commit/be7c3034108473beda214fd1d7c98fd6a7a3bdf5).
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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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<|im_start|>system
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{system_prompt}<|im_end|>
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<|im_start|>user
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{prompt}<|im_end|>
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<|im_start|>assistant
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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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| [s1.1-7B-Q2_K.gguf](https://huggingface.co/tensorblock/s1.1-7B-GGUF/blob/main/s1.1-7B-Q2_K.gguf) | Q2_K | 3.016 GB | smallest, significant quality loss - not recommended for most purposes |
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| [s1.1-7B-Q3_K_S.gguf](https://huggingface.co/tensorblock/s1.1-7B-GGUF/blob/main/s1.1-7B-Q3_K_S.gguf) | Q3_K_S | 3.492 GB | very small, high quality loss |
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| [s1.1-7B-Q3_K_M.gguf](https://huggingface.co/tensorblock/s1.1-7B-GGUF/blob/main/s1.1-7B-Q3_K_M.gguf) | Q3_K_M | 3.808 GB | very small, high quality loss |
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| [s1.1-7B-Q3_K_L.gguf](https://huggingface.co/tensorblock/s1.1-7B-GGUF/blob/main/s1.1-7B-Q3_K_L.gguf) | Q3_K_L | 4.088 GB | small, substantial quality loss |
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| [s1.1-7B-Q4_0.gguf](https://huggingface.co/tensorblock/s1.1-7B-GGUF/blob/main/s1.1-7B-Q4_0.gguf) | Q4_0 | 4.431 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
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| [s1.1-7B-Q4_K_S.gguf](https://huggingface.co/tensorblock/s1.1-7B-GGUF/blob/main/s1.1-7B-Q4_K_S.gguf) | Q4_K_S | 4.458 GB | small, greater quality loss |
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| [s1.1-7B-Q4_K_M.gguf](https://huggingface.co/tensorblock/s1.1-7B-GGUF/blob/main/s1.1-7B-Q4_K_M.gguf) | Q4_K_M | 4.683 GB | medium, balanced quality - recommended |
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| [s1.1-7B-Q5_0.gguf](https://huggingface.co/tensorblock/s1.1-7B-GGUF/blob/main/s1.1-7B-Q5_0.gguf) | Q5_0 | 5.315 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
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| [s1.1-7B-Q5_K_S.gguf](https://huggingface.co/tensorblock/s1.1-7B-GGUF/blob/main/s1.1-7B-Q5_K_S.gguf) | Q5_K_S | 5.315 GB | large, low quality loss - recommended |
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| [s1.1-7B-Q5_K_M.gguf](https://huggingface.co/tensorblock/s1.1-7B-GGUF/blob/main/s1.1-7B-Q5_K_M.gguf) | Q5_K_M | 5.445 GB | large, very low quality loss - recommended |
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| [s1.1-7B-Q6_K.gguf](https://huggingface.co/tensorblock/s1.1-7B-GGUF/blob/main/s1.1-7B-Q6_K.gguf) | Q6_K | 6.254 GB | very large, extremely low quality loss |
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| [s1.1-7B-Q8_0.gguf](https://huggingface.co/tensorblock/s1.1-7B-GGUF/blob/main/s1.1-7B-Q8_0.gguf) | Q8_0 | 8.099 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/s1.1-7B-GGUF --include "s1.1-7B-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/s1.1-7B-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
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```
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s1.1-7B-Q2_K.gguf
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version https://git-lfs.github.com/spec/v1
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oid sha256:86bcbf3c2f0a5d08cb22e7e4db4076ece4c3ceb933319e0e26bd033c8183a6d5
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size 3015940416
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version https://git-lfs.github.com/spec/v1
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oid sha256:d7f15b59d9293e30d21bf03b6ad35f7c58d483f3d42aa35da6c6be0d40488c7c
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size 4088459584
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version https://git-lfs.github.com/spec/v1
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oid sha256:1c1cf0b2cf357a84dda65465f234e212058ed6376211ca8cc35beb63f6829b61
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size 3808391488
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s1.1-7B-Q3_K_S.gguf
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version https://git-lfs.github.com/spec/v1
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oid sha256:ff0627631951ce14dac55fbe414d798bdab5cbbf455206ee1861aa748c817d12
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size 3492368704
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version https://git-lfs.github.com/spec/v1
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oid sha256:df62d572470ad04f167f81e5482e14b53d64d2197b49de944be67a6d9429bdee
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size 4431391040
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version https://git-lfs.github.com/spec/v1
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oid sha256:607f394dd4fef9d39a00abe4b68427759de9c80e4cd33a23b73f100a9f5c10a0
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size 4683073856
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version https://git-lfs.github.com/spec/v1
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oid sha256:8f09015a334a7749a207e336748e596f3e5955a7cc88607981ea12734554d06b
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size 4457769280
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version https://git-lfs.github.com/spec/v1
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oid sha256:5495176a9ed66a76147573c68ed4e2fe392ff70ea9ace5e8c0a4f9cd77141bea
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size 5315176768
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version https://git-lfs.github.com/spec/v1
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oid sha256:c60e8d8783b57a774eaec718ef2f9ce57019afbb72411f619222b57873e0cca1
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size 5444831552
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version https://git-lfs.github.com/spec/v1
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oid sha256:6340d0a5c2cf8433ffa584f59318e9bac3b2e458b65c7192e3d0b521e5400ca9
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size 5315176768
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version https://git-lfs.github.com/spec/v1
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oid sha256:71cbc23b3d5159f7c765f4cd0838707b5df9d23c11b4443066a03c623aa7d3f8
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size 6254199104
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s1.1-7B-Q8_0.gguf
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version https://git-lfs.github.com/spec/v1
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oid sha256:723d3d713b0e8a06efa2669ffe009414064675c65b3c5f1252729dd0a59281b0
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size 8098525504
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