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---
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.
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|
|