File size: 5,124 Bytes
fe7bdb5 edac28b fe7bdb5 edac28b fe7bdb5 edac28b fe7bdb5 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 |
---
license: mit
datasets:
- oscar-corpus/OSCAR-2301
- allenai/nllb
- Helsinki-NLP/opus-100
language:
- en
- da
- nl
- de
- is
- 'no'
- sc
- af
- ca
- ro
- gl
- it
- pt
- es
- bg
- mk
- sr
- uk
- ru
- id
- ms
- th
- vi
- mg
- fr
- hu
- el
- cs
- pl
- lt
- lv
- ka
- zh
- ja
- ko
- fi
- et
- gu
- hi
- mr
- ne
- ur
- az
- kk
- ky
- tr
- uz
- ar
- he
- fa
base_model: haoranxu/X-ALMA-13B-Pretrain
tags:
- TensorBlock
- GGUF
---
<div style="width: auto; margin-left: auto; margin-right: auto">
<img src="https://i.imgur.com/jC7kdl8.jpeg" alt="TensorBlock" style="width: 100%; min-width: 400px; display: block; margin: auto;">
</div>
<div style="display: flex; justify-content: space-between; width: 100%;">
<div style="display: flex; flex-direction: column; align-items: flex-start;">
<p style="margin-top: 0.5em; margin-bottom: 0em;">
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>
</p>
</div>
</div>
## haoranxu/X-ALMA-13B-Pretrain - GGUF
This repo contains GGUF format model files for [haoranxu/X-ALMA-13B-Pretrain](https://huggingface.co/haoranxu/X-ALMA-13B-Pretrain).
The files were quantized using machines provided by [TensorBlock](https://tensorblock.co/), and they are compatible with llama.cpp as of [commit b4011](https://github.com/ggerganov/llama.cpp/commit/a6744e43e80f4be6398fc7733a01642c846dce1d).
<div style="text-align: left; margin: 20px 0;">
<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;">
Run them on the TensorBlock client using your local machine ↗
</a>
</div>
## Prompt template
```
<s>[INST] <<SYS>>
{system_prompt}
<</SYS>>
{prompt} [/INST]
```
## Model file specification
| Filename | Quant type | File Size | Description |
| -------- | ---------- | --------- | ----------- |
| [X-ALMA-13B-Pretrain-Q2_K.gguf](https://huggingface.co/tensorblock/X-ALMA-13B-Pretrain-GGUF/blob/main/X-ALMA-13B-Pretrain-Q2_K.gguf) | Q2_K | 4.521 GB | smallest, significant quality loss - not recommended for most purposes |
| [X-ALMA-13B-Pretrain-Q3_K_S.gguf](https://huggingface.co/tensorblock/X-ALMA-13B-Pretrain-GGUF/blob/main/X-ALMA-13B-Pretrain-Q3_K_S.gguf) | Q3_K_S | 5.270 GB | very small, high quality loss |
| [X-ALMA-13B-Pretrain-Q3_K_M.gguf](https://huggingface.co/tensorblock/X-ALMA-13B-Pretrain-GGUF/blob/main/X-ALMA-13B-Pretrain-Q3_K_M.gguf) | Q3_K_M | 5.903 GB | very small, high quality loss |
| [X-ALMA-13B-Pretrain-Q3_K_L.gguf](https://huggingface.co/tensorblock/X-ALMA-13B-Pretrain-GGUF/blob/main/X-ALMA-13B-Pretrain-Q3_K_L.gguf) | Q3_K_L | 6.454 GB | small, substantial quality loss |
| [X-ALMA-13B-Pretrain-Q4_0.gguf](https://huggingface.co/tensorblock/X-ALMA-13B-Pretrain-GGUF/blob/main/X-ALMA-13B-Pretrain-Q4_0.gguf) | Q4_0 | 6.860 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| [X-ALMA-13B-Pretrain-Q4_K_S.gguf](https://huggingface.co/tensorblock/X-ALMA-13B-Pretrain-GGUF/blob/main/X-ALMA-13B-Pretrain-Q4_K_S.gguf) | Q4_K_S | 6.913 GB | small, greater quality loss |
| [X-ALMA-13B-Pretrain-Q4_K_M.gguf](https://huggingface.co/tensorblock/X-ALMA-13B-Pretrain-GGUF/blob/main/X-ALMA-13B-Pretrain-Q4_K_M.gguf) | Q4_K_M | 7.326 GB | medium, balanced quality - recommended |
| [X-ALMA-13B-Pretrain-Q5_0.gguf](https://huggingface.co/tensorblock/X-ALMA-13B-Pretrain-GGUF/blob/main/X-ALMA-13B-Pretrain-Q5_0.gguf) | Q5_0 | 8.356 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| [X-ALMA-13B-Pretrain-Q5_K_S.gguf](https://huggingface.co/tensorblock/X-ALMA-13B-Pretrain-GGUF/blob/main/X-ALMA-13B-Pretrain-Q5_K_S.gguf) | Q5_K_S | 8.356 GB | large, low quality loss - recommended |
| [X-ALMA-13B-Pretrain-Q5_K_M.gguf](https://huggingface.co/tensorblock/X-ALMA-13B-Pretrain-GGUF/blob/main/X-ALMA-13B-Pretrain-Q5_K_M.gguf) | Q5_K_M | 8.596 GB | large, very low quality loss - recommended |
| [X-ALMA-13B-Pretrain-Q6_K.gguf](https://huggingface.co/tensorblock/X-ALMA-13B-Pretrain-GGUF/blob/main/X-ALMA-13B-Pretrain-Q6_K.gguf) | Q6_K | 9.946 GB | very large, extremely low quality loss |
| [X-ALMA-13B-Pretrain-Q8_0.gguf](https://huggingface.co/tensorblock/X-ALMA-13B-Pretrain-GGUF/blob/main/X-ALMA-13B-Pretrain-Q8_0.gguf) | Q8_0 | 12.881 GB | very large, extremely low quality loss - not recommended |
## Downloading instruction
### Command line
Firstly, install Huggingface Client
```shell
pip install -U "huggingface_hub[cli]"
```
Then, downoad the individual model file the a local directory
```shell
huggingface-cli download tensorblock/X-ALMA-13B-Pretrain-GGUF --include "X-ALMA-13B-Pretrain-Q2_K.gguf" --local-dir MY_LOCAL_DIR
```
If you wanna download multiple model files with a pattern (e.g., `*Q4_K*gguf`), you can try:
```shell
huggingface-cli download tensorblock/X-ALMA-13B-Pretrain-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
```
|