README.md

---
language:
- en
- id
- jv
- su
license: gemma
tags:
- merge
- mergekit
- autoquant
- gguf
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
formerly gemma2-9b-cpt-sahabatai-v1-instruct-BaseTIES (model name too long :D )

![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 (number one for Gemma2-9B based model) on HF's Open LLM Leaderboard (with Merge/MoErges hide model unchecked) 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|