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---
base_model: []
library_name: transformers
tags:
- mergekit
- merge
- alpaca
- mistral
- not-for-all-audiences
- nsfw
license: cc-by-nc-4.0
---
# IceTeaRP-7b-8.0bpw-exl2
8.0bpw-h6-exl2 quant of [icefog72/IceTeaRP-7b](https://huggingface.co/icefog72/IceTeaRP-7b)
31/03/24 change in config.json
"rope_theta": 100000.0 => "rope_theta": 60000.0
## Merge Details
Just cooking mergers.
Prompt template: Alpaca
### Merge Method
This model was merged using the SLERP merge method.
### Models Merged
The following models were included in the merge:
* [icefog72/Kunokukulemonchini-7b](https://huggingface.co/icefog72/Kunokukulemonchini-7b)
* BigLM7-7b SLERP merge of
* [liminerity/M7-7](https://huggingface.co/liminerity/M7-7)
* [Undi95/BigL-7B](https://huggingface.co/Undi95/BigL-7B)
## How to download From the command line
I recommend using the `huggingface-hub` Python library:
```shell
pip3 install huggingface-hub
```
To download the `main` branch to a folder called `IceTeaRP-7b-8.0bpw-exl2`:
```shell
mkdir IceTeaRP-7b-8.0bpw-exl2
huggingface-cli download icefog72/IceTeaRP-7b-8.0bpw-exl2 --local-dir IceTeaRP-7b-8.0bpw-exl2 --local-dir-use-symlinks False
```
<details>
<summary>More advanced huggingface-cli download usage</summary>
If you remove the `--local-dir-use-symlinks False` parameter, the files will instead be stored in the central Hugging Face cache directory (default location on Linux is: `~/.cache/huggingface`), and symlinks will be added to the specified `--local-dir`, pointing to their real location in the cache. This allows for interrupted downloads to be resumed, and allows you to quickly clone the repo to multiple places on disk without triggering a download again. The downside, and the reason why I don't list that as the default option, is that the files are then hidden away in a cache folder and it's harder to know where your disk space is being used, and to clear it up if/when you want to remove a download model.
The cache location can be changed with the `HF_HOME` environment variable, and/or the `--cache-dir` parameter to `huggingface-cli`.
For more documentation on downloading with `huggingface-cli`, please see: [HF -> Hub Python Library -> Download files -> Download from the CLI](https://huggingface.co/docs/huggingface_hub/guides/download#download-from-the-cli).
To accelerate downloads on fast connections (1Gbit/s or higher), install `hf_transfer`:
```shell
pip3 install hf_transfer
```
And set environment variable `HF_HUB_ENABLE_HF_TRANSFER` to `1`:
```shell
mkdir FOLDERNAME
HF_HUB_ENABLE_HF_TRANSFER=1 huggingface-cli download MODEL --local-dir FOLDERNAME --local-dir-use-symlinks False
```
Windows Command Line users: You can set the environment variable by running `set HF_HUB_ENABLE_HF_TRANSFER=1` before the download command.
</details>
### Configuration
The following YAML configuration was used to produce this model:
```yaml
slices:
- sources:
- model: Kunokukulemonchini-7b
layer_range: [0, 32]
- model: BigLM7-7b
layer_range: [0, 32]
merge_method: slerp
base_model: Kunokukulemonchini-7b
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: float16
``` |