README.md

---
license: apache-2.0
tags:
- mergekit
- merge
- solar
base_model:
- upstage/SOLAR-10.7B-Instruct-v1.0
- NousResearch/Nous-Hermes-2-SOLAR-10.7B
model-index:
- name: franken-SOLAR-18B-v1.0
  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: 65.53
      name: normalized accuracy
    source:
      url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=vicgalle/franken-SOLAR-18B-v1.0
      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: 86.45
      name: normalized accuracy
    source:
      url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=vicgalle/franken-SOLAR-18B-v1.0
      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: 63.72
      name: accuracy
    source:
      url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=vicgalle/franken-SOLAR-18B-v1.0
      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: 62.14
    source:
      url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=vicgalle/franken-SOLAR-18B-v1.0
      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: 78.53
      name: accuracy
    source:
      url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=vicgalle/franken-SOLAR-18B-v1.0
      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: 45.79
      name: accuracy
    source:
      url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=vicgalle/franken-SOLAR-18B-v1.0
      name: Open LLM Leaderboard
---
# vicgalle/franken-SOLAR-18B-v1.0

This is a SOLAR-like model upscaled to 18B. 
It is a frankenmerge model created using mergekit, alternating layers of Nous-Hermes-2-SOLAR-10.7B and SOLAR-10.7B-Instruct.

![image/png](https://cdn-uploads.huggingface.co/production/uploads/5fad8602b8423e1d80b8a965/mMyHMuuftG71_o4at5suy.png)

Evaluations coming soon! 

This model has very good writing capabilities (compared to SOLAR-10.7B), specially for role-playing.

Quantized GGUF variants here https://huggingface.co./vicgalle/franken-SOLAR-18B-v1.0-GGUF

## Merge Details
### Merge Method

This model was merged using the passthrough merge method.

### Models Merged

The following models were included in the merge:
* [upstage/SOLAR-10.7B-Instruct-v1.0](https://huggingface.co./upstage/SOLAR-10.7B-Instruct-v1.0)
* [NousResearch/Nous-Hermes-2-SOLAR-10.7B](https://huggingface.co./NousResearch/Nous-Hermes-2-SOLAR-10.7B)

### Configuration

The following YAML configuration was used to produce this model:

```yaml
slices:
  - sources:
    - model: NousResearch/Nous-Hermes-2-SOLAR-10.7B
      layer_range: [0, 12]
  - sources:
    - model: upstage/SOLAR-10.7B-Instruct-v1.0
      layer_range: [6, 18]
  - sources:
    - model: NousResearch/Nous-Hermes-2-SOLAR-10.7B
      layer_range: [13, 25]
  - sources:
    - model: upstage/SOLAR-10.7B-Instruct-v1.0
      layer_range: [19, 31]
  - sources:
    - model: NousResearch/Nous-Hermes-2-SOLAR-10.7B
      layer_range: [26, 38]
  - sources:
    - model: upstage/SOLAR-10.7B-Instruct-v1.0
      layer_range: [32, 44]
  - sources:
    - model: NousResearch/Nous-Hermes-2-SOLAR-10.7B
      layer_range: [39, 48]
    
merge_method: passthrough
dtype: float16

```


### Usage

You can use the provided template:

```
tokenizer = AutoTokenizer.from_pretrained("vicgalle/franken-SOLAR-18B-v1.0")
model = AutoModelForCausalLM.from_pretrained("vicgalle/franken-SOLAR-18B-v1.0", torch_dtype=torch.float16, load_in_4bit=True)

conversation = [ {'role': 'system', 'content': SYSTEM_PROMPT}, {'role': 'user', 'content': USER_PROMPT} ] 
prompt = tokenizer.apply_chat_template(conversation, tokenize=False, add_generation_prompt=True)
inputs = tokenizer(prompt, return_tensors="pt").to(model.device)

outputs = model.generate(**inputs, use_cache=True, max_new_tokens=1024, do_sample=True, temperature=0.8)
output_text = tokenizer.decode(outputs[0]) 
```

# [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_vicgalle__franken-SOLAR-18B-v1.0)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |67.03|
|AI2 Reasoning Challenge (25-Shot)|65.53|
|HellaSwag (10-Shot)              |86.45|
|MMLU (5-Shot)                    |63.72|
|TruthfulQA (0-shot)              |62.14|
|Winogrande (5-shot)              |78.53|
|GSM8k (5-shot)                   |45.79|