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metadata
pipeline_tag: text-generation
base_model: bigcode/starcoder2-15b
datasets:
  - bigcode/self-oss-instruct-sc2-exec-filter-50k
license: bigcode-openrail-m
library_name: transformers
tags:
  - code
model-index:
  - name: starcoder2-15b-instruct-v0.1
    results:
      - task:
          type: text-generation
        dataset:
          name: LiveCodeBench (code generation)
          type: livecodebench-codegeneration
        metrics:
          - type: pass@1
            value: 20.4
      - task:
          type: text-generation
        dataset:
          name: LiveCodeBench (self repair)
          type: livecodebench-selfrepair
        metrics:
          - type: pass@1
            value: 20.9
      - task:
          type: text-generation
        dataset:
          name: LiveCodeBench (test output prediction)
          type: livecodebench-testoutputprediction
        metrics:
          - type: pass@1
            value: 29.8
      - task:
          type: text-generation
        dataset:
          name: LiveCodeBench (code execution)
          type: livecodebench-codeexecution
        metrics:
          - type: pass@1
            value: 28.1
      - task:
          type: text-generation
        dataset:
          name: HumanEval
          type: humaneval
        metrics:
          - type: pass@1
            value: 72.6
      - task:
          type: text-generation
        dataset:
          name: HumanEval+
          type: humanevalplus
        metrics:
          - type: pass@1
            value: 63.4
      - task:
          type: text-generation
        dataset:
          name: MBPP
          type: mbpp
        metrics:
          - type: pass@1
            value: 75.2
      - task:
          type: text-generation
        dataset:
          name: MBPP+
          type: mbppplus
        metrics:
          - type: pass@1
            value: 61.2
      - task:
          type: text-generation
        dataset:
          name: DS-1000
          type: ds-1000
        metrics:
          - type: pass@1
            value: 40.6
quantized_by: bartowski

Exllama v2 Quantizations of starcoder2-15b-instruct-v0.1

Using turboderp's ExLlamaV2 v0.0.20 for quantization.

The "main" branch only contains the measurement.json, download one of the other branches for the model (see below)

Each branch contains an individual bits per weight, with the main one containing only the meaurement.json for further conversions.

Original model: https://huggingface.co/bigcode/starcoder2-15b-instruct-v0.1

Prompt format

<|endoftext|>You are an exceptionally intelligent coding assistant that consistently delivers accurate and reliable responses to user instructions.

### Instruction
{prompt}

### Response
<|endoftext|>

Available sizes

Branch Bits lm_head bits VRAM (4k) VRAM (16k) VRAM (32k) Description
8_0 8.0 8.0 15.8 GB 16.8 GB 18.1 GB Maximum quality that ExLlamaV2 can produce, near unquantized performance.
6_5 6.5 8.0 13.9 GB 14.9 GB 16.2 GB Near unquantized performance at vastly reduced size, recommended.
5_0 5.0 6.0 11.0 GB 12.0 GB 13.2 GB Slightly lower quality vs 6.5.
4_25 4.25 6.0 9.5 GB 10.5 GB 11.8 GB GPTQ equivalent bits per weight.
3_5 3.5 6.0 8.1 GB 9.1 GB 10.4 GB Lower quality, not recommended.

Download instructions

With git:

git clone --single-branch --branch 6_5 https://huggingface.co/bartowski/starcoder2-15b-instruct-v0.1-exl2 starcoder2-15b-instruct-v0.1-exl2-6_5

With huggingface hub (credit to TheBloke for instructions):

pip3 install huggingface-hub

To download a specific branch, use the --revision parameter. For example, to download the 6.5 bpw branch:

Linux:

huggingface-cli download bartowski/starcoder2-15b-instruct-v0.1-exl2 --revision 6_5 --local-dir starcoder2-15b-instruct-v0.1-exl2-6_5 --local-dir-use-symlinks False

Windows (which apparently doesn't like _ in folders sometimes?):

huggingface-cli download bartowski/starcoder2-15b-instruct-v0.1-exl2 --revision 6_5 --local-dir starcoder2-15b-instruct-v0.1-exl2-6.5 --local-dir-use-symlinks False

Want to support my work? Visit my ko-fi page here: https://ko-fi.com/bartowski