---
language:
- en
- id
- jv
- su
license: gemma
tags:
- merge
- mergekit
base_model:
- GoToCompany/gemma2-9b-cpt-sahabatai-v1-instruct
- aisingapore/gemma2-9b-cpt-sea-lionv3-instruct
model-index:
- name: gemma2-9b-sahabatai-v1-instruct-BaseTIES
  results:
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: IFEval (0-Shot)
      type: HuggingFaceH4/ifeval
      args:
        num_few_shot: 0
    metrics:
    - type: inst_level_strict_acc and prompt_level_strict_acc
      value: 73.78
      name: strict accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=gmonsoon/gemma2-9b-sahabatai-v1-instruct-BaseTIES
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: BBH (3-Shot)
      type: BBH
      args:
        num_few_shot: 3
    metrics:
    - type: acc_norm
      value: 43.4
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=gmonsoon/gemma2-9b-sahabatai-v1-instruct-BaseTIES
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: MATH Lvl 5 (4-Shot)
      type: hendrycks/competition_math
      args:
        num_few_shot: 4
    metrics:
    - type: exact_match
      value: 19.34
      name: exact match
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=gmonsoon/gemma2-9b-sahabatai-v1-instruct-BaseTIES
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: GPQA (0-shot)
      type: Idavidrein/gpqa
      args:
        num_few_shot: 0
    metrics:
    - type: acc_norm
      value: 9.4
      name: acc_norm
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=gmonsoon/gemma2-9b-sahabatai-v1-instruct-BaseTIES
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: MuSR (0-shot)
      type: TAUR-Lab/MuSR
      args:
        num_few_shot: 0
    metrics:
    - type: acc_norm
      value: 19.13
      name: acc_norm
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=gmonsoon/gemma2-9b-sahabatai-v1-instruct-BaseTIES
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: MMLU-PRO (5-shot)
      type: TIGER-Lab/MMLU-Pro
      config: main
      split: test
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 37.19
      name: accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=gmonsoon/gemma2-9b-sahabatai-v1-instruct-BaseTIES
      name: Open LLM Leaderboard
---

# SahabatAI-Lion-9B-TIES-v1

![image/png](https://cdn-uploads.huggingface.co/production/uploads/642b04e4ecec03b44649e318/rJ0ogty-DbLUEH48Ms5lE.png)

Based on some research, when a finetuned model is merged with its base model with TIES method, there is possibility the merged model will achieve better output. 

UPDATE!!! as 20 November 2024, this model is third best model on HF's Open LLM Leaderboard (with Merge/MoErges checked) for LLM model below 10B parameters.

![image/png](https://cdn-uploads.huggingface.co/production/uploads/642b04e4ecec03b44649e318/8Hv3YtWtzzFlJ0_kUpsT7.png)

gmonsoon/SahabatAI-Lion-9B-TIES-v1 is a merge of the following models:
* [GoToCompany/gemma2-9b-cpt-sahabatai-v1-instruct](https://huggingface.co/GoToCompany/gemma2-9b-cpt-sahabatai-v1-instruct)
* [aisingapore/gemma2-9b-cpt-sea-lionv3-instruct](https://huggingface.co/aisingapore/gemma2-9b-cpt-sea-lionv3-instruct)

DEMO Spaces: [HERE](https://huggingface.co/spaces/gmonsoon/SahabatAI-Lion-9B-TIES-v1)

## 🧩 Configuration

```yaml
models:
  - model: GoToCompany/gemma2-9b-cpt-sahabatai-v1-instruct
    parameters:
      weight: 1
      density: 1
  - model: GoToCompany/gemma2-9b-cpt-sahabatai-v1-instruct
    parameters:
      weight: 1
      density: 1
merge_method: ties
base_model: aisingapore/gemma2-9b-cpt-sea-lionv3-instruct
parameters:
  density: 1
  normalize: true
  int8_mask: true
dtype: bfloat16
```

## 💻 Usage

```python
!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "gmonsoon/SahabatAI-Lion-9B-TIES-v1"
messages = [{"role": "user", "content": "What is a large language model?"}]

tokenizer = AutoTokenizer.from_pretrained(model)
prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
pipeline = transformers.pipeline(
    "text-generation",
    model=model,
    torch_dtype=torch.float16,
    device_map="auto",
)

outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
print(outputs[0]["generated_text"])
```
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_gmonsoon__gemma2-9b-sahabatai-v1-instruct-BaseTIES)

|      Metric       |Value|
|-------------------|----:|
|Avg.               |33.70|
|IFEval (0-Shot)    |73.78|
|BBH (3-Shot)       |43.40|
|MATH Lvl 5 (4-Shot)|19.34|
|GPQA (0-shot)      | 9.40|
|MuSR (0-shot)      |19.13|
|MMLU-PRO (5-shot)  |37.19|