Downloads · 30 days
206
6% of all-time downloads
grimjim/llama-3-Nephilim-v3-8B
llama-3-Nephilim-v3-8B is a text generation model from grimjim. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as cc-by-nc-4.0.
This repo contains a merge of pre-trained language models created using mergekit.
Downloads · 30 days
206
6% of all-time downloads
All-time downloads
3.5K
Public
Parameters
8B
32.1 GB on disk
Likes
15
Public
Click a slice to open those files.
.safetensors16.1 GB · 100%
From the Hugging Face model README
This repo contains a merge of pre-trained language models created using mergekit.
GGUF quants are here.
Although none of the components of this merge were trained for roleplay nor intended for it, the model can be used effectively in that role.
Tested with temperature 1 and minP 0.01. This model leans toward being creative, so adjust temperature upward or downward as desired.
There are initial format consistency issues with the merged model, but this can be mitigated in an Instruct prompt. Additionally, promptsteering was employed to vary the text generation output to avoid some of the common failings observed during text generation with Llama 3 8B models. The complete Instruct prompt used during testing is available below.
Built with Meta Llama 3.
This model was merged using the task arithmetic merge method using grimjim/Llama-3-Instruct-8B-SPPO-Iter3-SimPO-merge as a base.
The following models were included in the merge:
The following YAML configuration was used to produce this model:
base_model: grimjim/Llama-3-Instruct-8B-SPPO-Iter3-SimPO-merge
dtype: bfloat16
merge_method: task_arithmetic
parameters:
normalize: false
slices:
- sources:
- layer_range: [0, 32]
model: grimjim/Llama-3-Instruct-8B-SPPO-Iter3-SimPO-merge
- layer_range: [0, 32]
model: tokyotech-llm/Llama-3-Swallow-8B-Instruct-v0.1
parameters:
weight: 0.1
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 20.54 |
| IFEval (0-Shot) | 41.74 |
| BBH (3-Shot) | 28.96 |
| MATH Lvl 5 (4-Shot) | 9.14 |
| GPQA (0-shot) | 6.04 |
| MuSR (0-shot) | 8.33 |
| MMLU-PRO (5-shot) | 29.02 |