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gagan3012_-_MetaModel-gguf
RichardErkhov/gagan3012_-_MetaModel-gguf
gagan3012_-_MetaModel-gguf is a machine learning model from RichardErkhov. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
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At a glance
- Access
- Public
- Created
- Aug 30, 2024
- Updated
- Aug 31, 2024
- SHA
- dee5b031
Model card
From the Hugging Face model README
Quantization made by Richard Erkhov.
MetaModel - GGUF
- Model creator: https://huggingface.co/gagan3012/
- Original model: https://huggingface.co/gagan3012/MetaModel/
| Name | Quant method | Size |
|---|---|---|
| MetaModel.Q2_K.gguf | Q2_K | 3.73GB |
| MetaModel.IQ3_XS.gguf | IQ3_XS | 4.14GB |
| MetaModel.IQ3_S.gguf | IQ3_S | 4.37GB |
| MetaModel.Q3_K_S.gguf | Q3_K_S | 4.34GB |
| MetaModel.IQ3_M.gguf | IQ3_M | 4.51GB |
| MetaModel.Q3_K.gguf | Q3_K | 4.84GB |
| MetaModel.Q3_K_M.gguf | Q3_K_M | 4.84GB |
| MetaModel.Q3_K_L.gguf | Q3_K_L | 5.26GB |
| MetaModel.IQ4_XS.gguf | IQ4_XS | 5.43GB |
| MetaModel.Q4_0.gguf | Q4_0 | 5.66GB |
| MetaModel.IQ4_NL.gguf | IQ4_NL | 5.72GB |
| MetaModel.Q4_K_S.gguf | Q4_K_S | 5.7GB |
| MetaModel.Q4_K.gguf | Q4_K | 6.02GB |
| MetaModel.Q4_K_M.gguf | Q4_K_M | 6.02GB |
| MetaModel.Q4_1.gguf | Q4_1 | 6.27GB |
| MetaModel.Q5_0.gguf | Q5_0 | 6.89GB |
| MetaModel.Q5_K_S.gguf | Q5_K_S | 6.89GB |
| MetaModel.Q5_K.gguf | Q5_K | 7.08GB |
| MetaModel.Q5_K_M.gguf | Q5_K_M | 7.08GB |
| MetaModel.Q5_1.gguf | Q5_1 | 7.51GB |
| MetaModel.Q6_K.gguf | Q6_K | 8.2GB |
| MetaModel.Q8_0.gguf | Q8_0 | 10.62GB |
Original model description:
license: apache-2.0 tags:
- merge
- mergekit
MetaModel
This model is a merge of the following models made with mergekit:
🧩 Configuration
slices:
- sources:
- model: jeonsworld/CarbonVillain-en-10.7B-v4
layer_range: [0, 48]
- model: kekmodel/StopCarbon-10.7B-v5
layer_range: [0, 48]
merge_method: slerp
base_model: jeonsworld/CarbonVillain-en-10.7B-v4
parameters:
t:
- filter: self_attn
value: [0, 0.5, 0.3, 0.7, 1]
- filter: mlp
value: [1, 0.5, 0.7, 0.3, 0]
- value: 0.5
dtype: bfloat16
Dataset Card for Evaluation run of gagan3012/MetaModel
<!-- Provide a quick summary of the dataset. -->Dataset automatically created during the evaluation run of model gagan3012/MetaModel on the Open LLM Leaderboard.
The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results.
An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).
To load the details from a run, you can for instance do the following:
from datasets import load_dataset
data = load_dataset("open-llm-leaderboard/details_gagan3012__MetaModel",
"harness_winogrande_5",
split="train")
Latest results
These are the latest results from run 2024-01-04T14:09:43.780941(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval):
{
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}
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 74.4 |
| ARC (25-shot) | 71.08 |
| HellaSwag (10-shot) | 88.45 |
| MMLU (5-shot) | 66.26 |
| TruthfulQA (0-shot) | 71.84 |
| Winogrande (5-shot) | 83.43 |
| GSM8K (5-shot) | 65.35 |
- Created
- Aug 30, 2024
- Updated
- Aug 31, 2024