README.md

---
license: mit
tags:
- mergekit
- merge
- code
base_model:
- codellama/CodeLlama-70b-Instruct-hf
pipeline_tag: conversational
model-index:
- name: BigCodeLlama-92b
  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: 54.78
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=nisten/BigCodeLlama-92b
      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: 77.84
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=nisten/BigCodeLlama-92b
      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: 55.4
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=nisten/BigCodeLlama-92b
      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: 51.34
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=nisten/BigCodeLlama-92b
      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: 73.09
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=nisten/BigCodeLlama-92b
      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: 44.96
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=nisten/BigCodeLlama-92b
      name: Open LLM Leaderboard
---
# BigCodeLLama 92b LFG 🚀

## Experimental 92B CodeLlaMA frankenstein to see how it benchmarks

### Models Merged with base ```codellama/CodeLlama-70b-Instruct-hf```



### Models Merged

The following models were included in the merge:
* ../CodeLlama-70b-Python-hf
* ../CodeLlama-70b-Instruct-hf

### Configuration

The following YAML configuration was used to produce this model:

```yaml
dtype: bfloat16
merge_method: passthrough
slices:
- sources:
  - layer_range: [0, 69]
    model:
      model:
        path: ../CodeLlama-70b-Instruct-hf
- sources:
  - layer_range: [42, 80]
    model:
      model:
        path: ../CodeLlama-70b-Python-hf
```
Gguf available here https://huggingface.co/nisten/BigCodeLlama-92b-GGUF
# [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_nisten__BigCodeLlama-92b)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |59.57|
|AI2 Reasoning Challenge (25-Shot)|54.78|
|HellaSwag (10-Shot)              |77.84|
|MMLU (5-Shot)                    |55.40|
|TruthfulQA (0-shot)              |51.34|
|Winogrande (5-shot)              |73.09|
|GSM8k (5-shot)                   |44.96|