README.md

---
base_model:
- icefog72/Kunokukulemonchini-7b
- icefog72/BigLM7-7b
- liminerity/M7-7b
- Undi95/BigL-7B
library_name: transformers
tags:
- mergekit
- merge
- alpaca
- mistral
- not-for-all-audiences
- nsfw
license: cc-by-nc-4.0
model-index:
- name: IceTeaRP-7b
  results:
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: AI2 Reasoning Challenge (25-Shot)
      type: ai2_arc
      config: ARC-Challenge
      split: test
      args:
        num_few_shot: 25
    metrics:
    - type: acc_norm
      value: 66.98
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=icefog72/IceTeaRP-7b
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: HellaSwag (10-Shot)
      type: hellaswag
      split: validation
      args:
        num_few_shot: 10
    metrics:
    - type: acc_norm
      value: 86.13
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=icefog72/IceTeaRP-7b
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: MMLU (5-Shot)
      type: cais/mmlu
      config: all
      split: test
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 63.97
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=icefog72/IceTeaRP-7b
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: TruthfulQA (0-shot)
      type: truthful_qa
      config: multiple_choice
      split: validation
      args:
        num_few_shot: 0
    metrics:
    - type: mc2
      value: 62.44
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=icefog72/IceTeaRP-7b
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: Winogrande (5-shot)
      type: winogrande
      config: winogrande_xl
      split: validation
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 78.85
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=icefog72/IceTeaRP-7b
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: GSM8k (5-shot)
      type: gsm8k
      config: main
      split: test
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 60.20
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=icefog72/IceTeaRP-7b
      name: Open LLM Leaderboard
---

## Advertisement

- Check out new merge model without repetition problem [IceLemonTeaRP-32k-7b](https://huggingface.co/icefog72/IceLemonTeaRP-32k-7b)
# IceTeaRP-7b
![image/png](https://cdn-uploads.huggingface.co/production/uploads/63407b719dbfe0d48b2d763b/JVUyMYUx-lgmrnmePUxyJ.png)

This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).

- 4.0bpw-h6 [IceTeaRP-7b-4.0bpw-exl2](https://huggingface.co/icefog72/IceTeaRP-7b-4.0bpw-exl2) 
- 4.2bpw-h6 [IceTeaRP-7b-4.2bpw-exl2](https://huggingface.co/icefog72/IceTeaRP-7b-4.2bpw-exl2)
- 6.5bpw-h6 [IceTeaRP-7b-6.5bpw-exl2](https://huggingface.co/icefog72/IceTeaRP-7b-6.5bpw-exl2)
- 8.0bpw-h6 [IceTeaRP-7b-8.0bpw-exl2](https://huggingface.co/icefog72/IceTeaRP-7b-8.0bpw-exl2)


Thanks mradermacher for [IceTeaRP-7b-GGUF](https://huggingface.co/mradermacher/IceTeaRP-7b-GGUF)
 
## Merge Details

Just cooking mergers. For my taste, it came out better than Kunokukulemonchini-7b. Model capable of handling 32k context window without any scaling.

Prompt template: Alpaca

measurement.json for quanting exl2 included.
### Users test feedback

Can develop repetition problem at 16k-32k without good RP rules/CoT in promt.

You can try edit "rope_theta": 100000.0 => "rope_theta": 60000.0 to make it even more slightly coherent(hard to find balance).



### 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/M7-7b](https://huggingface.co/liminerity/M7-7b)
  * [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`:

```shell
mkdir IceTeaRP-7b
huggingface-cli download icefog72/IceTeaRP-7b --local-dir IceTeaRP-7b --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
```
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_icefog72__IceTeaRP-7b)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |69.76|
|AI2 Reasoning Challenge (25-Shot)|66.98|
|HellaSwag (10-Shot)              |86.13|
|MMLU (5-Shot)                    |63.97|
|TruthfulQA (0-shot)              |62.44|
|Winogrande (5-shot)              |78.85|
|GSM8k (5-shot)                   |60.20|