measurement.json
Browse files- README.md +126 -0
- measurement.json +0 -0
README.md
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---
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pipeline_tag: text-generation
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inference:
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parameters:
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temperature: 0.2
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top_p: 0.95
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widget:
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- text: 'def print_hello_world():'
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example_title: Hello world
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group: Python
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datasets:
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- bigcode/the-stack-v2-train
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license: bigcode-openrail-m
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library_name: transformers
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tags:
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- code
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model-index:
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- name: starcoder2-7b
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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: CruxEval-I
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type: cruxeval-i
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metrics:
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- type: pass@1
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value: 34.6
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- task:
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type: text-generation
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dataset:
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name: DS-1000
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type: ds-1000
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metrics:
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- type: pass@1
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value: 27.8
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- task:
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type: text-generation
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dataset:
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name: GSM8K (PAL)
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type: gsm8k-pal
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metrics:
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- type: accuracy
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value: 40.4
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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: humanevalplus
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metrics:
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- type: pass@1
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value: 29.9
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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: humaneval
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metrics:
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- type: pass@1
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value: 35.4
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- task:
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type: text-generation
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dataset:
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name: RepoBench-v1.1
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type: repobench-v1.1
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metrics:
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- type: edit-smiliarity
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value: 72.07
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quantized_by: bartowski
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---
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## Exllama v2 Quantizations of starcoder2-7b
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Using <a href="https://github.com/turboderp/exllamav2/releases/tag/v0.0.14">turboderp's ExLlamaV2 v0.0.14</a> for quantization.
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<b>The "main" branch only contains the measurement.json, download one of the other branches for the model (see below)</b>
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Each branch contains an individual bits per weight, with the main one containing only the meaurement.json for further conversions.
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Original model: https://huggingface.co/bigcode/starcoder2-7b
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| Branch | Bits | lm_head bits | VRAM (4k) | VRAM (16k) | VRAM (32k) | Description |
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| ----- | ---- | ------- | ------ | ------ | ------ | ------------ |
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| [8_0](https://huggingface.co/bartowski/starcoder2-7b-exl2/tree/8_0) | 8.0 | 8.0 | 8.4 GB | 9.8 GB | 11.8 GB | Maximum quality that ExLlamaV2 can produce, near unquantized performance. |
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| [6_5](https://huggingface.co/bartowski/starcoder2-7b-exl2/tree/6_5) | 6.5 | 8.0 | 7.2 GB | 8.6 GB | 10.6 GB | Very similar to 8.0, good tradeoff of size vs performance, **recommended**. |
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| [5_0](https://huggingface.co/bartowski/starcoder2-7b-exl2/tree/5_0) | 5.0 | 6.0 | 6.0 GB | 7.4 GB | 9.4 GB | Slightly lower quality vs 6.5, but usable on 8GB cards. |
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| [4_25](https://huggingface.co/bartowski/starcoder2-7b-exl2/tree/4_25) | 4.25 | 6.0 | 5.3 GB | 6.7 GB | 8.7 GB | GPTQ equivalent bits per weight, slightly higher quality. |
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| [3_5](https://huggingface.co/bartowski/starcoder2-7b-exl2/tree/3_5) | 3.5 | 6.0 | 4.7 GB | 6.1 GB | 8.1 GB | Lower quality, only use if you have to. |
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## Download instructions
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With git:
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```shell
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git clone --single-branch --branch 6_5 https://huggingface.co/bartowski/starcoder2-7b-exl2 starcoder2-7b-exl2-6_5
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```
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With huggingface hub (credit to TheBloke for instructions):
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```shell
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pip3 install huggingface-hub
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```
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To download the `main` (only useful if you only care about measurement.json) branch to a folder called `starcoder2-7b-exl2`:
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```shell
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mkdir starcoder2-7b-exl2
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huggingface-cli download bartowski/starcoder2-7b-exl2 --local-dir starcoder2-7b-exl2 --local-dir-use-symlinks False
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```
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To download from a different branch, add the `--revision` parameter:
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Linux:
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```shell
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mkdir starcoder2-7b-exl2-6_5
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huggingface-cli download bartowski/starcoder2-7b-exl2 --revision 6_5 --local-dir starcoder2-7b-exl2-6_5 --local-dir-use-symlinks False
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```
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Windows (which apparently doesn't like _ in folders sometimes?):
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```shell
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mkdir starcoder2-7b-exl2-6.5
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huggingface-cli download bartowski/starcoder2-7b-exl2 --revision 6_5 --local-dir starcoder2-7b-exl2-6.5 --local-dir-use-symlinks False
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```
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Want to support my work? Visit my ko-fi page here: https://ko-fi.com/bartowski
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measurement.json
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