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Browse files- .gitattributes +12 -0
- Dolphin3.0-Mistral-24B-Q2_K.gguf +3 -0
- Dolphin3.0-Mistral-24B-Q3_K_L.gguf +3 -0
- Dolphin3.0-Mistral-24B-Q3_K_M.gguf +3 -0
- Dolphin3.0-Mistral-24B-Q3_K_S.gguf +3 -0
- Dolphin3.0-Mistral-24B-Q4_0.gguf +3 -0
- Dolphin3.0-Mistral-24B-Q4_K_M.gguf +3 -0
- Dolphin3.0-Mistral-24B-Q4_K_S.gguf +3 -0
- Dolphin3.0-Mistral-24B-Q5_0.gguf +3 -0
- Dolphin3.0-Mistral-24B-Q5_K_M.gguf +3 -0
- Dolphin3.0-Mistral-24B-Q5_K_S.gguf +3 -0
- Dolphin3.0-Mistral-24B-Q6_K.gguf +3 -0
- Dolphin3.0-Mistral-24B-Q8_0.gguf +3 -0
- README.md +97 -0
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README.md
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| 1 |
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---
|
| 2 |
+
datasets:
|
| 3 |
+
- OpenCoder-LLM/opc-sft-stage1
|
| 4 |
+
- OpenCoder-LLM/opc-sft-stage2
|
| 5 |
+
- microsoft/orca-agentinstruct-1M-v1
|
| 6 |
+
- microsoft/orca-math-word-problems-200k
|
| 7 |
+
- NousResearch/hermes-function-calling-v1
|
| 8 |
+
- AI-MO/NuminaMath-CoT
|
| 9 |
+
- AI-MO/NuminaMath-TIR
|
| 10 |
+
- allenai/tulu-3-sft-mixture
|
| 11 |
+
- cognitivecomputations/dolphin-coder
|
| 12 |
+
- HuggingFaceTB/smoltalk
|
| 13 |
+
- cognitivecomputations/samantha-data
|
| 14 |
+
- m-a-p/CodeFeedback-Filtered-Instruction
|
| 15 |
+
- m-a-p/Code-Feedback
|
| 16 |
+
language:
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| 17 |
+
- en
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| 18 |
+
base_model: cognitivecomputations/Dolphin3.0-Mistral-24B
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| 19 |
+
pipeline_tag: text-generation
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| 20 |
+
library_name: transformers
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| 21 |
+
tags:
|
| 22 |
+
- TensorBlock
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| 23 |
+
- GGUF
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| 24 |
+
---
|
| 25 |
+
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| 26 |
+
<div style="width: auto; margin-left: auto; margin-right: auto">
|
| 27 |
+
<img src="https://i.imgur.com/jC7kdl8.jpeg" alt="TensorBlock" style="width: 100%; min-width: 400px; display: block; margin: auto;">
|
| 28 |
+
</div>
|
| 29 |
+
<div style="display: flex; justify-content: space-between; width: 100%;">
|
| 30 |
+
<div style="display: flex; flex-direction: column; align-items: flex-start;">
|
| 31 |
+
<p style="margin-top: 0.5em; margin-bottom: 0em;">
|
| 32 |
+
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>
|
| 33 |
+
</p>
|
| 34 |
+
</div>
|
| 35 |
+
</div>
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| 36 |
+
|
| 37 |
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## cognitivecomputations/Dolphin3.0-Mistral-24B - GGUF
|
| 38 |
+
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| 39 |
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This repo contains GGUF format model files for [cognitivecomputations/Dolphin3.0-Mistral-24B](https://huggingface.co/cognitivecomputations/Dolphin3.0-Mistral-24B).
|
| 40 |
+
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| 41 |
+
The files were quantized using machines provided by [TensorBlock](https://tensorblock.co/), and they are compatible with llama.cpp as of [commit b4823](https://github.com/ggml-org/llama.cpp/commit/5bbe6a9fe9a8796a9389c85accec89dbc4d91e39).
|
| 42 |
+
|
| 43 |
+
<div style="text-align: left; margin: 20px 0;">
|
| 44 |
+
<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;">
|
| 45 |
+
Run them on the TensorBlock client using your local machine ↗
|
| 46 |
+
</a>
|
| 47 |
+
</div>
|
| 48 |
+
|
| 49 |
+
## Prompt template
|
| 50 |
+
|
| 51 |
+
```
|
| 52 |
+
<|im_start|>system
|
| 53 |
+
{system_prompt}<|im_end|>
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| 54 |
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<|im_start|>user
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| 55 |
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{prompt}<|im_end|>
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| 56 |
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<|im_start|>assistant
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| 57 |
+
```
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| 58 |
+
|
| 59 |
+
## Model file specification
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| 60 |
+
|
| 61 |
+
| Filename | Quant type | File Size | Description |
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| 62 |
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| -------- | ---------- | --------- | ----------- |
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| 63 |
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| [Dolphin3.0-Mistral-24B-Q2_K.gguf](https://huggingface.co/tensorblock/Dolphin3.0-Mistral-24B-GGUF/blob/main/Dolphin3.0-Mistral-24B-Q2_K.gguf) | Q2_K | 8.890 GB | smallest, significant quality loss - not recommended for most purposes |
|
| 64 |
+
| [Dolphin3.0-Mistral-24B-Q3_K_S.gguf](https://huggingface.co/tensorblock/Dolphin3.0-Mistral-24B-GGUF/blob/main/Dolphin3.0-Mistral-24B-Q3_K_S.gguf) | Q3_K_S | 10.400 GB | very small, high quality loss |
|
| 65 |
+
| [Dolphin3.0-Mistral-24B-Q3_K_M.gguf](https://huggingface.co/tensorblock/Dolphin3.0-Mistral-24B-GGUF/blob/main/Dolphin3.0-Mistral-24B-Q3_K_M.gguf) | Q3_K_M | 11.474 GB | very small, high quality loss |
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| 66 |
+
| [Dolphin3.0-Mistral-24B-Q3_K_L.gguf](https://huggingface.co/tensorblock/Dolphin3.0-Mistral-24B-GGUF/blob/main/Dolphin3.0-Mistral-24B-Q3_K_L.gguf) | Q3_K_L | 12.401 GB | small, substantial quality loss |
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| 67 |
+
| [Dolphin3.0-Mistral-24B-Q4_0.gguf](https://huggingface.co/tensorblock/Dolphin3.0-Mistral-24B-GGUF/blob/main/Dolphin3.0-Mistral-24B-Q4_0.gguf) | Q4_0 | 13.442 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
|
| 68 |
+
| [Dolphin3.0-Mistral-24B-Q4_K_S.gguf](https://huggingface.co/tensorblock/Dolphin3.0-Mistral-24B-GGUF/blob/main/Dolphin3.0-Mistral-24B-Q4_K_S.gguf) | Q4_K_S | 13.549 GB | small, greater quality loss |
|
| 69 |
+
| [Dolphin3.0-Mistral-24B-Q4_K_M.gguf](https://huggingface.co/tensorblock/Dolphin3.0-Mistral-24B-GGUF/blob/main/Dolphin3.0-Mistral-24B-Q4_K_M.gguf) | Q4_K_M | 14.334 GB | medium, balanced quality - recommended |
|
| 70 |
+
| [Dolphin3.0-Mistral-24B-Q5_0.gguf](https://huggingface.co/tensorblock/Dolphin3.0-Mistral-24B-GGUF/blob/main/Dolphin3.0-Mistral-24B-Q5_0.gguf) | Q5_0 | 16.304 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
|
| 71 |
+
| [Dolphin3.0-Mistral-24B-Q5_K_S.gguf](https://huggingface.co/tensorblock/Dolphin3.0-Mistral-24B-GGUF/blob/main/Dolphin3.0-Mistral-24B-Q5_K_S.gguf) | Q5_K_S | 16.304 GB | large, low quality loss - recommended |
|
| 72 |
+
| [Dolphin3.0-Mistral-24B-Q5_K_M.gguf](https://huggingface.co/tensorblock/Dolphin3.0-Mistral-24B-GGUF/blob/main/Dolphin3.0-Mistral-24B-Q5_K_M.gguf) | Q5_K_M | 16.764 GB | large, very low quality loss - recommended |
|
| 73 |
+
| [Dolphin3.0-Mistral-24B-Q6_K.gguf](https://huggingface.co/tensorblock/Dolphin3.0-Mistral-24B-GGUF/blob/main/Dolphin3.0-Mistral-24B-Q6_K.gguf) | Q6_K | 19.346 GB | very large, extremely low quality loss |
|
| 74 |
+
| [Dolphin3.0-Mistral-24B-Q8_0.gguf](https://huggingface.co/tensorblock/Dolphin3.0-Mistral-24B-GGUF/blob/main/Dolphin3.0-Mistral-24B-Q8_0.gguf) | Q8_0 | 25.055 GB | very large, extremely low quality loss - not recommended |
|
| 75 |
+
|
| 76 |
+
|
| 77 |
+
## Downloading instruction
|
| 78 |
+
|
| 79 |
+
### Command line
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| 80 |
+
|
| 81 |
+
Firstly, install Huggingface Client
|
| 82 |
+
|
| 83 |
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```shell
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| 84 |
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pip install -U "huggingface_hub[cli]"
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| 85 |
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```
|
| 86 |
+
|
| 87 |
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Then, downoad the individual model file the a local directory
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| 88 |
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|
| 89 |
+
```shell
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| 90 |
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huggingface-cli download tensorblock/Dolphin3.0-Mistral-24B-GGUF --include "Dolphin3.0-Mistral-24B-Q2_K.gguf" --local-dir MY_LOCAL_DIR
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| 91 |
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```
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| 92 |
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| 93 |
+
If you wanna download multiple model files with a pattern (e.g., `*Q4_K*gguf`), you can try:
|
| 94 |
+
|
| 95 |
+
```shell
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| 96 |
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huggingface-cli download tensorblock/Dolphin3.0-Mistral-24B-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
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| 97 |
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```
|