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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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---
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pipeline_tag: text-generation
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inference: false
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license: apache-2.0
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library_name: transformers
|
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tags:
|
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- TensorBlock
|
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- GGUF
|
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base_model: ibm/PowerLM-3b
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model-index:
|
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- name: ibm/PowerLM-3b
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results:
|
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- task:
|
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type: text-generation
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dataset:
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name: ARC
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type: lm-eval-harness
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metrics:
|
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- type: accuracy-norm
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value: 60.5
|
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name: accuracy-norm
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verified: false
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- type: accuracy
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value: 72.0
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name: accuracy
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verified: false
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- type: accuracy-norm
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value: 74.6
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name: accuracy-norm
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verified: false
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+
- type: accuracy-norm
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value: 43.6
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name: accuracy-norm
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34 |
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verified: false
|
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- type: accuracy-norm
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value: 79.9
|
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name: accuracy-norm
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verified: false
|
39 |
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- type: accuracy-norm
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value: 70.0
|
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name: accuracy-norm
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verified: false
|
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- type: accuracy
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value: 49.2
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name: accuracy
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verified: false
|
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- type: accuracy
|
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value: 34.9
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name: accuracy
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verified: false
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- type: accuracy
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value: 15.2
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name: accuracy
|
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verified: false
|
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- task:
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type: text-generation
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dataset:
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name: humaneval
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type: bigcode-eval
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metrics:
|
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- type: pass@1
|
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value: 26.8
|
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name: pass@1
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verified: false
|
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+
- type: pass@1
|
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value: 33.6
|
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name: pass@1
|
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verified: false
|
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---
|
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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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## ibm/PowerLM-3b - GGUF
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|
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This repo contains GGUF format model files for [ibm/PowerLM-3b](https://huggingface.co/ibm/PowerLM-3b).
|
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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 b4011](https://github.com/ggerganov/llama.cpp/commit/a6744e43e80f4be6398fc7733a01642c846dce1d).
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|
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## Prompt template
|
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|
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```
|
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|
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```
|
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|
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## Model file specification
|
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|
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| Filename | Quant type | File Size | Description |
|
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| -------- | ---------- | --------- | ----------- |
|
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| [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 |
|
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| [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 |
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| [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 |
|
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+
| [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 |
|
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+
| [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 |
|
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+
| [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 |
|
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+
| [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 |
|
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+
|
111 |
+
|
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## Downloading instruction
|
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+
|
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### Command line
|
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+
|
116 |
+
Firstly, install Huggingface Client
|
117 |
+
|
118 |
+
```shell
|
119 |
+
pip install -U "huggingface_hub[cli]"
|
120 |
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```
|
121 |
+
|
122 |
+
Then, downoad the individual model file the a local directory
|
123 |
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|
124 |
+
```shell
|
125 |
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huggingface-cli download tensorblock/PowerLM-3b-GGUF --include "PowerLM-3b-Q2_K.gguf" --local-dir MY_LOCAL_DIR
|
126 |
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```
|
127 |
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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:
|
129 |
+
|
130 |
+
```shell
|
131 |
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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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```
|