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--- |
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license: cc |
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tags: |
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- mergekit |
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- merge |
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base_model: |
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- macadeliccc/MBX-7B-v3-DPO |
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- mlabonne/OmniBeagle-7B |
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model-index: |
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- name: OmniCorso-7B |
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results: |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: AI2 Reasoning Challenge (25-Shot) |
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type: ai2_arc |
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config: ARC-Challenge |
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split: test |
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args: |
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num_few_shot: 25 |
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metrics: |
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- type: acc_norm |
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value: 72.7 |
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name: normalized accuracy |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=macadeliccc/OmniCorso-7B |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: HellaSwag (10-Shot) |
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type: hellaswag |
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split: validation |
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args: |
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num_few_shot: 10 |
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metrics: |
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- type: acc_norm |
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value: 88.7 |
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name: normalized accuracy |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=macadeliccc/OmniCorso-7B |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: MMLU (5-Shot) |
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type: cais/mmlu |
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config: all |
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split: test |
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args: |
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num_few_shot: 5 |
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metrics: |
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- type: acc |
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value: 64.91 |
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name: accuracy |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=macadeliccc/OmniCorso-7B |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: TruthfulQA (0-shot) |
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type: truthful_qa |
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config: multiple_choice |
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split: validation |
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args: |
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num_few_shot: 0 |
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metrics: |
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- type: mc2 |
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value: 73.43 |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=macadeliccc/OmniCorso-7B |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: Winogrande (5-shot) |
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type: winogrande |
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config: winogrande_xl |
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split: validation |
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args: |
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num_few_shot: 5 |
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metrics: |
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- type: acc |
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value: 83.74 |
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name: accuracy |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=macadeliccc/OmniCorso-7B |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: GSM8k (5-shot) |
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type: gsm8k |
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config: main |
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split: test |
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args: |
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num_few_shot: 5 |
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metrics: |
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- type: acc |
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value: 70.96 |
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name: accuracy |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=macadeliccc/OmniCorso-7B |
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name: Open LLM Leaderboard |
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--- |
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# OmniCorso-7B |
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## Code Example |
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```python |
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from transformers import AutoModelForCausalLM, AutoTokenizer |
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tokenizer = AutoTokenizer.from_pretrained("macadeliccc/OmniCorso-7B") |
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model = AutoModelForCausalLM.from_pretrained("macadeliccc/OmniCorso-7B") |
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messages = [ |
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{"role": "system", "content": "Respond to the users request like a pirate"}, |
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{"role": "user", "content": "Can you write me a quicksort algorithm?"} |
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] |
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gen_input = tokenizer.apply_chat_template(messages, return_tensors="pt") |
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``` |
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The following models were included in the merge: |
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* [macadeliccc/MBX-7B-v3-DPO](https://huggingface.co/macadeliccc/MBX-7B-v3-DPO) |
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* [mlabonne/OmniBeagle-7B](https://huggingface.co/mlabonne/OmniBeagle-7B) |
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### Configuration |
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The following YAML configuration was used to produce this model: |
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```yaml |
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slices: |
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- sources: |
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- model: mlabonne/OmniBeagle-7B |
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layer_range: [0, 32] |
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- model: macadeliccc/MBX-7B-v3-DPO |
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layer_range: [0, 32] |
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merge_method: slerp |
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base_model: macadeliccc/MBX-7B-v3-DPO |
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parameters: |
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t: |
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- filter: self_attn |
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value: [0, 0.5, 0.3, 0.7, 1] |
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- filter: mlp |
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value: [1, 0.5, 0.7, 0.3, 0] |
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- value: 0.5 |
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dtype: bfloat16 |
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``` |
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## Quantizations |
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### GGUF |
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+ [iMatrix](https://huggingface.co/macadeliccc/OmniCorso-7B-GGUF) |
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### Exllamav2 |
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Quants are available thanks to user bartowski, check them out [here](https://huggingface.co/bartowski/OmniCorso-7B-exl2) |
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| Branch | Bits | lm_head bits | VRAM (4k) | VRAM (16k) | VRAM (32k) | Description | |
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| ----- | ---- | ------- | ------ | ------ | ------ | ------------ | |
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| [8_0](https://huggingface.co/bartowski/OmniCorso-7B-exl2/tree/8_0) | 8.0 | 8.0 | 8.4 GB | 9.8 GB | 11.8 GB | Maximum quality that ExLlamaV2 can produce, near unquantized performance. | |
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| [6_5](https://huggingface.co/bartowski/OmniCorso-7B-exl2/tree/6_5) | 6.5 | 8.0 | 7.2 GB | 8.6 GB | 10.6 GB | Very similar to 8.0, good tradeoff of size vs performance, **recommended**. | |
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| [5_0](https://huggingface.co/bartowski/OmniCorso-7B-exl2/tree/5_0) | 5.0 | 6.0 | 6.0 GB | 7.4 GB | 9.4 GB | Slightly lower quality vs 6.5, but usable on 8GB cards. | |
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| [4_25](https://huggingface.co/bartowski/OmniCorso-7B-exl2/tree/4_25) | 4.25 | 6.0 | 5.3 GB | 6.7 GB | 8.7 GB | GPTQ equivalent bits per weight, slightly higher quality. | |
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| [3_5](https://huggingface.co/bartowski/OmniCorso-7B-exl2/tree/3_5) | 3.5 | 6.0 | 4.7 GB | 6.1 GB | 8.1 GB | Lower quality, only use if you have to. | |
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## Evaluations |
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<pre>----Benchmark Complete---- |
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2024-02-11 15:34:40 |
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Time taken: 178.3 mins |
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Prompt Format: ChatML |
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Model: macadeliccc/OmniCorso-7B |
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Score (v2): 73.75 |
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Parseable: 167.0 |
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--------------- |
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Batch completed |
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Time taken: 178.3 mins |
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--------------- |
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</pre> |
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| Model |AGIEval|GPT4All|TruthfulQA|Bigbench|Average| |
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|---------------------------------------------------------------|------:|------:|---------:|-------:|------:| |
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|[OmniCorso-7B](https://huggingface.co/macadeliccc/OmniCorso-7B)| 45.89| 77.66| 74.12| 49.24| 61.73| |
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### AGIEval |
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| Task |Version| Metric |Value| |Stderr| |
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|------------------------------|------:|--------|----:|---|-----:| |
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|agieval_aqua_rat | 0|acc |29.13|± | 2.86| |
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| | |acc_norm|27.17|± | 2.80| |
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|agieval_logiqa_en | 0|acc |39.32|± | 1.92| |
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| | |acc_norm|39.63|± | 1.92| |
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|agieval_lsat_ar | 0|acc |23.91|± | 2.82| |
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| | |acc_norm|23.91|± | 2.82| |
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|agieval_lsat_lr | 0|acc |53.14|± | 2.21| |
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| | |acc_norm|53.92|± | 2.21| |
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|agieval_lsat_rc | 0|acc |66.54|± | 2.88| |
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| | |acc_norm|67.29|± | 2.87| |
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|agieval_sat_en | 0|acc |80.58|± | 2.76| |
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| | |acc_norm|80.58|± | 2.76| |
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|agieval_sat_en_without_passage| 0|acc |45.63|± | 3.48| |
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| | |acc_norm|43.69|± | 3.46| |
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|agieval_sat_math | 0|acc |33.18|± | 3.18| |
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| | |acc_norm|30.91|± | 3.12| |
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Average: 45.89% |
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### GPT4All |
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| Task |Version| Metric |Value| |Stderr| |
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|-------------|------:|--------|----:|---|-----:| |
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|arc_challenge| 0|acc |67.32|± | 1.37| |
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| | |acc_norm|68.43|± | 1.36| |
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|arc_easy | 0|acc |87.46|± | 0.68| |
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| | |acc_norm|83.50|± | 0.76| |
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|boolq | 1|acc |88.13|± | 0.57| |
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|hellaswag | 0|acc |68.47|± | 0.46| |
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| | |acc_norm|86.96|± | 0.34| |
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|openbookqa | 0|acc |38.80|± | 2.18| |
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| | |acc_norm|50.00|± | 2.24| |
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|piqa | 0|acc |83.03|± | 0.88| |
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| | |acc_norm|85.31|± | 0.83| |
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|winogrande | 0|acc |81.29|± | 1.10| |
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Average: 77.66% |
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### TruthfulQA |
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| Task |Version|Metric|Value| |Stderr| |
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|-------------|------:|------|----:|---|-----:| |
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|truthfulqa_mc| 1|mc1 |58.26|± | 1.73| |
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| | |mc2 |74.12|± | 1.43| |
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Average: 74.12% |
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### Bigbench |
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| Task |Version| Metric |Value| |Stderr| |
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|------------------------------------------------|------:|---------------------|----:|---|-----:| |
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|bigbench_causal_judgement | 0|multiple_choice_grade|56.84|± | 3.60| |
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|bigbench_date_understanding | 0|multiple_choice_grade|63.41|± | 2.51| |
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|bigbench_disambiguation_qa | 0|multiple_choice_grade|49.22|± | 3.12| |
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|bigbench_geometric_shapes | 0|multiple_choice_grade|23.96|± | 2.26| |
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| | |exact_str_match | 1.39|± | 0.62| |
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|bigbench_logical_deduction_five_objects | 0|multiple_choice_grade|34.20|± | 2.12| |
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|bigbench_logical_deduction_seven_objects | 0|multiple_choice_grade|23.71|± | 1.61| |
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|bigbench_logical_deduction_three_objects | 0|multiple_choice_grade|60.33|± | 2.83| |
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|bigbench_movie_recommendation | 0|multiple_choice_grade|49.00|± | 2.24| |
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|bigbench_navigate | 0|multiple_choice_grade|55.20|± | 1.57| |
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|bigbench_reasoning_about_colored_objects | 0|multiple_choice_grade|70.75|± | 1.02| |
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|bigbench_ruin_names | 0|multiple_choice_grade|55.80|± | 2.35| |
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|bigbench_salient_translation_error_detection | 0|multiple_choice_grade|36.97|± | 1.53| |
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|bigbench_snarks | 0|multiple_choice_grade|72.38|± | 3.33| |
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|bigbench_sports_understanding | 0|multiple_choice_grade|76.27|± | 1.36| |
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|bigbench_temporal_sequences | 0|multiple_choice_grade|54.50|± | 1.58| |
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|bigbench_tracking_shuffled_objects_five_objects | 0|multiple_choice_grade|23.12|± | 1.19| |
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|bigbench_tracking_shuffled_objects_seven_objects| 0|multiple_choice_grade|20.34|± | 0.96| |
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|bigbench_tracking_shuffled_objects_three_objects| 0|multiple_choice_grade|60.33|± | 2.83| |
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Average: 49.24% |
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Average score: 61.73% |
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Elapsed time: 02:20:06 |
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# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard) |
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Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_macadeliccc__OmniCorso-7B) |
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| Metric |Value| |
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|---------------------------------|----:| |
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|Avg. |75.74| |
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|AI2 Reasoning Challenge (25-Shot)|72.70| |
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|HellaSwag (10-Shot) |88.70| |
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|MMLU (5-Shot) |64.91| |
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|TruthfulQA (0-shot) |73.43| |
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|Winogrande (5-shot) |83.74| |
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|GSM8k (5-shot) |70.96| |
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