---
license: apache-2.0
tags:
- mergekit
- merge
- solar
base_model:
- upstage/SOLAR-10.7B-Instruct-v1.0
model-index:
- name: SOLAR-13B-Instruct-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: 57.25
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=vicgalle/SOLAR-13B-Instruct-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: 78.03
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=vicgalle/SOLAR-13B-Instruct-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: 55.75
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=vicgalle/SOLAR-13B-Instruct-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: 61.99
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=vicgalle/SOLAR-13B-Instruct-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: 70.24
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=vicgalle/SOLAR-13B-Instruct-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: 16.6
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=vicgalle/SOLAR-13B-Instruct-v1.0
      name: Open LLM Leaderboard
---
# SOLAR-13B-Instruct-v1.0

This is SOLAR-10.7B, but upscaled to 13B, to optimize VRAM usage of typical GPU cards (a 4bit quant fits in 12GB).

Evaluations coming soon!

This is a frankenmerge model created using [mergekit](https://github.com/cg123/mergekit).

## 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)

### Configuration

The following YAML configuration was used to produce this model:

```yaml
slices:
  - sources:
    - model: upstage/SOLAR-10.7B-Instruct-v1.0
      layer_range: [0, 28]
  - sources:
    - model: upstage/SOLAR-10.7B-Instruct-v1.0
      layer_range: [20, 48]
merge_method: passthrough
dtype: float16

```


### Prompt template

The same as in SOLAR-10.7B:

```
<s> ### User:
{prompt}

### Assistant:
{response}</s>
```
# [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__SOLAR-13B-Instruct-v1.0)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |56.65|
|AI2 Reasoning Challenge (25-Shot)|57.25|
|HellaSwag (10-Shot)              |78.03|
|MMLU (5-Shot)                    |55.75|
|TruthfulQA (0-shot)              |61.99|
|Winogrande (5-shot)              |70.24|
|GSM8k (5-shot)                   |16.60|