measurement.json
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- measurement.json +0 -0
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| 1 |
+
---
|
| 2 |
+
license: other
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| 3 |
+
license_name: llama-3
|
| 4 |
+
license_link: https://llama.meta.com/llama3/license/
|
| 5 |
+
tags:
|
| 6 |
+
- text-generation-inference
|
| 7 |
+
- transformers
|
| 8 |
+
- unsloth
|
| 9 |
+
- llama
|
| 10 |
+
datasets:
|
| 11 |
+
- Replete-AI/code_bagel_hermes-2.5
|
| 12 |
+
- Replete-AI/code_bagel
|
| 13 |
+
- Replete-AI/OpenHermes-2.5-Uncensored
|
| 14 |
+
- teknium/OpenHermes-2.5
|
| 15 |
+
- layoric/tiny-codes-alpaca
|
| 16 |
+
- glaiveai/glaive-code-assistant-v3
|
| 17 |
+
- ajibawa-2023/Code-290k-ShareGPT
|
| 18 |
+
- TIGER-Lab/MathInstruct
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| 19 |
+
- chargoddard/commitpack-ft-instruct-rated
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| 20 |
+
- iamturun/code_instructions_120k_alpaca
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| 21 |
+
- ise-uiuc/Magicoder-Evol-Instruct-110K
|
| 22 |
+
- cognitivecomputations/dolphin-coder
|
| 23 |
+
- nickrosh/Evol-Instruct-Code-80k-v1
|
| 24 |
+
- coseal/CodeUltraFeedback_binarized
|
| 25 |
+
- glaiveai/glaive-function-calling-v2
|
| 26 |
+
- CyberNative/Code_Vulnerability_Security_DPO
|
| 27 |
+
- jondurbin/airoboros-2.2
|
| 28 |
+
- camel-ai
|
| 29 |
+
- lmsys/lmsys-chat-1m
|
| 30 |
+
- CollectiveCognition/chats-data-2023-09-22
|
| 31 |
+
- CoT-Alpaca-GPT4
|
| 32 |
+
- WizardLM/WizardLM_evol_instruct_70k
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| 33 |
+
- WizardLM/WizardLM_evol_instruct_V2_196k
|
| 34 |
+
- teknium/GPT4-LLM-Cleaned
|
| 35 |
+
- GPTeacher
|
| 36 |
+
- OpenGPT
|
| 37 |
+
- meta-math/MetaMathQA
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| 38 |
+
- Open-Orca/SlimOrca
|
| 39 |
+
- garage-bAInd/Open-Platypus
|
| 40 |
+
- anon8231489123/ShareGPT_Vicuna_unfiltered
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| 41 |
+
- Unnatural-Instructions-GPT4
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| 42 |
+
model-index:
|
| 43 |
+
- name: Replete-Coder-llama3-8b
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| 44 |
+
results:
|
| 45 |
+
- task:
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| 46 |
+
name: HumanEval
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| 47 |
+
type: text-generation
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| 48 |
+
dataset:
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| 49 |
+
type: openai_humaneval
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| 50 |
+
name: HumanEval
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| 51 |
+
metrics:
|
| 52 |
+
- name: pass@1
|
| 53 |
+
type: pass@1
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| 54 |
+
value:
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| 55 |
+
verified: false
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| 56 |
+
- task:
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| 57 |
+
name: AI2 Reasoning Challenge
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| 58 |
+
type: text-generation
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| 59 |
+
dataset:
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| 60 |
+
name: AI2 Reasoning Challenge (25-Shot)
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| 61 |
+
type: ai2_arc
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| 62 |
+
config: ARC-Challenge
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| 63 |
+
split: test
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| 64 |
+
args:
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| 65 |
+
num_few_shot: 25
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| 66 |
+
metrics:
|
| 67 |
+
- type: accuracy
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| 68 |
+
value:
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| 69 |
+
name: normalized accuracy
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| 70 |
+
source:
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| 71 |
+
url: https://www.placeholderurl.com
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| 72 |
+
name: Open LLM Leaderboard
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| 73 |
+
- task:
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| 74 |
+
name: Text Generation
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| 75 |
+
type: text-generation
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| 76 |
+
dataset:
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| 77 |
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name: HellaSwag (10-Shot)
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| 78 |
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type: hellaswag
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| 79 |
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split: validation
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| 80 |
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args:
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| 81 |
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num_few_shot: 10
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| 82 |
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metrics:
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| 83 |
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- type: accuracy
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| 84 |
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value:
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| 85 |
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name: normalized accuracy
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| 86 |
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source:
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| 87 |
+
url: https://www.placeholderurl.com
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| 88 |
+
name: Open LLM Leaderboard
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| 89 |
+
- task:
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| 90 |
+
name: Text Generation
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| 91 |
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type: text-generation
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| 92 |
+
dataset:
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| 93 |
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name: MMLU (5-Shot)
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| 94 |
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type: cais/mmlu
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| 95 |
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config: all
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| 96 |
+
split: test
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| 97 |
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args:
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| 98 |
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num_few_shot: 5
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| 99 |
+
metrics:
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| 100 |
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- type: accuracy
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| 101 |
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value:
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| 102 |
+
name: accuracy
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| 103 |
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source:
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| 104 |
+
url: https://www.placeholderurl.com
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| 105 |
+
name: Open LLM Leaderboard
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| 106 |
+
- task:
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| 107 |
+
name: Text Generation
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| 108 |
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type: text-generation
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| 109 |
+
dataset:
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| 110 |
+
name: TruthfulQA (0-shot)
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| 111 |
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type: truthful_qa
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| 112 |
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config: multiple_choice
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| 113 |
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split: validation
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| 114 |
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args:
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| 115 |
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num_few_shot: 0
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| 116 |
+
metrics:
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| 117 |
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- type: multiple_choice_accuracy
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| 118 |
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value:
|
| 119 |
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source:
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| 120 |
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url: https://www.placeholderurl.com
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| 121 |
+
name: Open LLM Leaderboard
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| 122 |
+
- task:
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| 123 |
+
name: Text Generation
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| 124 |
+
type: text-generation
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| 125 |
+
dataset:
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| 126 |
+
name: Winogrande (5-shot)
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| 127 |
+
type: winogrande
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| 128 |
+
config: winogrande_xl
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| 129 |
+
split: validation
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| 130 |
+
args:
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| 131 |
+
num_few_shot: 5
|
| 132 |
+
metrics:
|
| 133 |
+
- type: accuracy
|
| 134 |
+
value:
|
| 135 |
+
name: accuracy
|
| 136 |
+
source:
|
| 137 |
+
url: https://www.placeholderurl.com
|
| 138 |
+
name: Open LLM Leaderboard
|
| 139 |
+
- task:
|
| 140 |
+
name: Text Generation
|
| 141 |
+
type: text-generation
|
| 142 |
+
dataset:
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| 143 |
+
name: GSM8k (5-shot)
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| 144 |
+
type: gsm8k
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| 145 |
+
config: main
|
| 146 |
+
split: test
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| 147 |
+
args:
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| 148 |
+
num_few_shot: 5
|
| 149 |
+
metrics:
|
| 150 |
+
- type: accuracy
|
| 151 |
+
value:
|
| 152 |
+
name: accuracy
|
| 153 |
+
source:
|
| 154 |
+
url: https://www.placeholderurl.com
|
| 155 |
+
name: Open LLM Leaderboard
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| 156 |
+
quantized_by: bartowski
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| 157 |
+
pipeline_tag: text-generation
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| 158 |
+
---
|
| 159 |
+
|
| 160 |
+
## Exllama v2 Quantizations of Replete-Coder-Llama3-8B
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| 161 |
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| 162 |
+
Using <a href="https://github.com/turboderp/exllamav2/releases/tag/v0.1.6">turboderp's ExLlamaV2 v0.1.6</a> for quantization.
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| 163 |
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| 164 |
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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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| 165 |
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| 166 |
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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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| 167 |
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| 168 |
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Original model: https://huggingface.co/Replete-AI/Replete-Coder-Llama3-8B
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| 169 |
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| 170 |
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## Prompt format
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| 171 |
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| 172 |
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No chat template specified so default is used. This may be incorrect, check original model card for details.
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| 173 |
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| 174 |
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```
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| 175 |
+
<|im_start|>system
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| 176 |
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{system_prompt}<|im_end|>
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| 177 |
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<|im_start|>user
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| 178 |
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{prompt}<|im_end|>
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| 179 |
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<|im_start|>assistant
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| 180 |
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| 181 |
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```
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| 182 |
+
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| 183 |
+
## Available sizes
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| 184 |
+
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| 185 |
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| 186 |
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| Branch | Bits | lm_head bits | VRAM (4k) | VRAM (8K) | VRAM (16k) | VRAM (32k) | Description |
|
| 187 |
+
| ----- | ---- | ------- | ------ | ------ | ------ | ------ | ------------ |
|
| 188 |
+
| [8_0](https://huggingface.co/bartowski/Replete-Coder-Llama3-8B-exl2/tree/8_0) | 8.0 | 8.0 | 10.1 GB | 10.5 GB | 11.5 GB | 13.6 GB | Maximum quality that ExLlamaV2 can produce, near unquantized performance. |
|
| 189 |
+
| [6_5](https://huggingface.co/bartowski/Replete-Coder-Llama3-8B-exl2/tree/6_5) | 6.5 | 8.0 | 8.9 GB | 9.3 GB | 10.3 GB | 12.4 GB | Very similar to 8.0, good tradeoff of size vs performance, **recommended**. |
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| 190 |
+
| [5_0](https://huggingface.co/bartowski/Replete-Coder-Llama3-8B-exl2/tree/5_0) | 5.0 | 6.0 | 7.7 GB | 8.1 GB | 9.1 GB | 11.2 GB | Slightly lower quality vs 6.5, but usable on 8GB cards. |
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| 191 |
+
| [4_25](https://huggingface.co/bartowski/Replete-Coder-Llama3-8B-exl2/tree/4_25) | 4.25 | 6.0 | 7.0 GB | 7.4 GB | 8.4 GB | 10.5 GB | GPTQ equivalent bits per weight, slightly higher quality. |
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| 192 |
+
| [3_5](https://huggingface.co/bartowski/Replete-Coder-Llama3-8B-exl2/tree/3_5) | 3.5 | 6.0 | 6.4 GB | 6.8 GB | 7.8 GB | 9.9 GB | Lower quality, only use if you have to. |
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| 193 |
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| 194 |
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## Download instructions
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| 195 |
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| 196 |
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With git:
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| 197 |
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| 198 |
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```shell
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| 199 |
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git clone --single-branch --branch 6_5 https://huggingface.co/bartowski/Replete-Coder-Llama3-8B-exl2 Replete-Coder-Llama3-8B-exl2-6_5
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| 200 |
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```
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| 201 |
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| 202 |
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With huggingface hub (credit to TheBloke for instructions):
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| 203 |
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| 204 |
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```shell
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| 205 |
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pip3 install huggingface-hub
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| 206 |
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```
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| 207 |
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| 208 |
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To download a specific branch, use the `--revision` parameter. For example, to download the 6.5 bpw branch:
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| 209 |
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| 210 |
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Linux:
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| 211 |
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|
| 212 |
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```shell
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| 213 |
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huggingface-cli download bartowski/Replete-Coder-Llama3-8B-exl2 --revision 6_5 --local-dir Replete-Coder-Llama3-8B-exl2-6_5
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| 214 |
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```
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| 215 |
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| 216 |
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Windows (which apparently doesn't like _ in folders sometimes?):
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| 217 |
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| 218 |
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```shell
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| 219 |
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huggingface-cli download bartowski/Replete-Coder-Llama3-8B-exl2 --revision 6_5 --local-dir Replete-Coder-Llama3-8B-exl2-6.5
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| 220 |
+
```
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| 221 |
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| 222 |
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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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