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Browse files- .gitattributes +12 -0
- PowerLM-3b-Q2_K.gguf +3 -0
- PowerLM-3b-Q3_K_L.gguf +3 -0
- PowerLM-3b-Q3_K_M.gguf +3 -0
- PowerLM-3b-Q3_K_S.gguf +3 -0
- PowerLM-3b-Q4_0.gguf +3 -0
- PowerLM-3b-Q4_K_M.gguf +3 -0
- PowerLM-3b-Q4_K_S.gguf +3 -0
- PowerLM-3b-Q5_0.gguf +3 -0
- PowerLM-3b-Q5_K_M.gguf +3 -0
- PowerLM-3b-Q5_K_S.gguf +3 -0
- PowerLM-3b-Q6_K.gguf +3 -0
- PowerLM-3b-Q8_0.gguf +3 -0
- README.md +132 -0
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README.md
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---
|
| 2 |
+
pipeline_tag: text-generation
|
| 3 |
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inference: false
|
| 4 |
+
license: apache-2.0
|
| 5 |
+
library_name: transformers
|
| 6 |
+
tags:
|
| 7 |
+
- TensorBlock
|
| 8 |
+
- GGUF
|
| 9 |
+
base_model: ibm/PowerLM-3b
|
| 10 |
+
model-index:
|
| 11 |
+
- name: ibm/PowerLM-3b
|
| 12 |
+
results:
|
| 13 |
+
- task:
|
| 14 |
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type: text-generation
|
| 15 |
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dataset:
|
| 16 |
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name: ARC
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| 17 |
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type: lm-eval-harness
|
| 18 |
+
metrics:
|
| 19 |
+
- type: accuracy-norm
|
| 20 |
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value: 60.5
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| 21 |
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name: accuracy-norm
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| 22 |
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verified: false
|
| 23 |
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- type: accuracy
|
| 24 |
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value: 72.0
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| 25 |
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name: accuracy
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| 26 |
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verified: false
|
| 27 |
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- type: accuracy-norm
|
| 28 |
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value: 74.6
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| 29 |
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name: accuracy-norm
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| 30 |
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verified: false
|
| 31 |
+
- type: accuracy-norm
|
| 32 |
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value: 43.6
|
| 33 |
+
name: accuracy-norm
|
| 34 |
+
verified: false
|
| 35 |
+
- type: accuracy-norm
|
| 36 |
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value: 79.9
|
| 37 |
+
name: accuracy-norm
|
| 38 |
+
verified: false
|
| 39 |
+
- type: accuracy-norm
|
| 40 |
+
value: 70.0
|
| 41 |
+
name: accuracy-norm
|
| 42 |
+
verified: false
|
| 43 |
+
- type: accuracy
|
| 44 |
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value: 49.2
|
| 45 |
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name: accuracy
|
| 46 |
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verified: false
|
| 47 |
+
- type: accuracy
|
| 48 |
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value: 34.9
|
| 49 |
+
name: accuracy
|
| 50 |
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verified: false
|
| 51 |
+
- type: accuracy
|
| 52 |
+
value: 15.2
|
| 53 |
+
name: accuracy
|
| 54 |
+
verified: false
|
| 55 |
+
- task:
|
| 56 |
+
type: text-generation
|
| 57 |
+
dataset:
|
| 58 |
+
name: humaneval
|
| 59 |
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type: bigcode-eval
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| 60 |
+
metrics:
|
| 61 |
+
- type: pass@1
|
| 62 |
+
value: 26.8
|
| 63 |
+
name: pass@1
|
| 64 |
+
verified: false
|
| 65 |
+
- type: pass@1
|
| 66 |
+
value: 33.6
|
| 67 |
+
name: pass@1
|
| 68 |
+
verified: false
|
| 69 |
+
---
|
| 70 |
+
|
| 71 |
+
<div style="width: auto; margin-left: auto; margin-right: auto">
|
| 72 |
+
<img src="https://i.imgur.com/jC7kdl8.jpeg" alt="TensorBlock" style="width: 100%; min-width: 400px; display: block; margin: auto;">
|
| 73 |
+
</div>
|
| 74 |
+
<div style="display: flex; justify-content: space-between; width: 100%;">
|
| 75 |
+
<div style="display: flex; flex-direction: column; align-items: flex-start;">
|
| 76 |
+
<p style="margin-top: 0.5em; margin-bottom: 0em;">
|
| 77 |
+
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>
|
| 78 |
+
</p>
|
| 79 |
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</div>
|
| 80 |
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</div>
|
| 81 |
+
|
| 82 |
+
## ibm/PowerLM-3b - GGUF
|
| 83 |
+
|
| 84 |
+
This repo contains GGUF format model files for [ibm/PowerLM-3b](https://huggingface.co/ibm/PowerLM-3b).
|
| 85 |
+
|
| 86 |
+
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).
|
| 87 |
+
|
| 88 |
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## Prompt template
|
| 89 |
+
|
| 90 |
+
```
|
| 91 |
+
|
| 92 |
+
```
|
| 93 |
+
|
| 94 |
+
## Model file specification
|
| 95 |
+
|
| 96 |
+
| Filename | Quant type | File Size | Description |
|
| 97 |
+
| -------- | ---------- | --------- | ----------- |
|
| 98 |
+
| [PowerLM-3b-Q2_K.gguf](https://huggingface.co/tensorblock/PowerLM-3b-GGUF/tree/main/PowerLM-3b-Q2_K.gguf) | Q2_K | 1.252 GB | smallest, significant quality loss - not recommended for most purposes |
|
| 99 |
+
| [PowerLM-3b-Q3_K_S.gguf](https://huggingface.co/tensorblock/PowerLM-3b-GGUF/tree/main/PowerLM-3b-Q3_K_S.gguf) | Q3_K_S | 1.453 GB | very small, high quality loss |
|
| 100 |
+
| [PowerLM-3b-Q3_K_M.gguf](https://huggingface.co/tensorblock/PowerLM-3b-GGUF/tree/main/PowerLM-3b-Q3_K_M.gguf) | Q3_K_M | 1.617 GB | very small, high quality loss |
|
| 101 |
+
| [PowerLM-3b-Q3_K_L.gguf](https://huggingface.co/tensorblock/PowerLM-3b-GGUF/tree/main/PowerLM-3b-Q3_K_L.gguf) | Q3_K_L | 1.759 GB | small, substantial quality loss |
|
| 102 |
+
| [PowerLM-3b-Q4_0.gguf](https://huggingface.co/tensorblock/PowerLM-3b-GGUF/tree/main/PowerLM-3b-Q4_0.gguf) | Q4_0 | 1.873 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
|
| 103 |
+
| [PowerLM-3b-Q4_K_S.gguf](https://huggingface.co/tensorblock/PowerLM-3b-GGUF/tree/main/PowerLM-3b-Q4_K_S.gguf) | Q4_K_S | 1.888 GB | small, greater quality loss |
|
| 104 |
+
| [PowerLM-3b-Q4_K_M.gguf](https://huggingface.co/tensorblock/PowerLM-3b-GGUF/tree/main/PowerLM-3b-Q4_K_M.gguf) | Q4_K_M | 2.001 GB | medium, balanced quality - recommended |
|
| 105 |
+
| [PowerLM-3b-Q5_0.gguf](https://huggingface.co/tensorblock/PowerLM-3b-GGUF/tree/main/PowerLM-3b-Q5_0.gguf) | Q5_0 | 2.269 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
|
| 106 |
+
| [PowerLM-3b-Q5_K_S.gguf](https://huggingface.co/tensorblock/PowerLM-3b-GGUF/tree/main/PowerLM-3b-Q5_K_S.gguf) | Q5_K_S | 2.269 GB | large, low quality loss - recommended |
|
| 107 |
+
| [PowerLM-3b-Q5_K_M.gguf](https://huggingface.co/tensorblock/PowerLM-3b-GGUF/tree/main/PowerLM-3b-Q5_K_M.gguf) | Q5_K_M | 2.334 GB | large, very low quality loss - recommended |
|
| 108 |
+
| [PowerLM-3b-Q6_K.gguf](https://huggingface.co/tensorblock/PowerLM-3b-GGUF/tree/main/PowerLM-3b-Q6_K.gguf) | Q6_K | 2.689 GB | very large, extremely low quality loss |
|
| 109 |
+
| [PowerLM-3b-Q8_0.gguf](https://huggingface.co/tensorblock/PowerLM-3b-GGUF/tree/main/PowerLM-3b-Q8_0.gguf) | Q8_0 | 3.481 GB | very large, extremely low quality loss - not recommended |
|
| 110 |
+
|
| 111 |
+
|
| 112 |
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## Downloading instruction
|
| 113 |
+
|
| 114 |
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### Command line
|
| 115 |
+
|
| 116 |
+
Firstly, install Huggingface Client
|
| 117 |
+
|
| 118 |
+
```shell
|
| 119 |
+
pip install -U "huggingface_hub[cli]"
|
| 120 |
+
```
|
| 121 |
+
|
| 122 |
+
Then, downoad the individual model file the a local directory
|
| 123 |
+
|
| 124 |
+
```shell
|
| 125 |
+
huggingface-cli download tensorblock/PowerLM-3b-GGUF --include "PowerLM-3b-Q2_K.gguf" --local-dir MY_LOCAL_DIR
|
| 126 |
+
```
|
| 127 |
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|
| 128 |
+
If you wanna download multiple model files with a pattern (e.g., `*Q4_K*gguf`), you can try:
|
| 129 |
+
|
| 130 |
+
```shell
|
| 131 |
+
huggingface-cli download tensorblock/PowerLM-3b-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
|
| 132 |
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```
|