Text Generation
Transformers
Safetensors
mixtral
Mixture of Experts
openchat/openchat-3.5-0106
giux78/zefiro-7b-beta-ITA-v0.1
azale-ai/Starstreak-7b-beta
gagan3012/Mistral_arabic_dpo
davidkim205/komt-mistral-7b-v1
OpenBuddy/openbuddy-zephyr-7b-v14.1
manishiitg/open-aditi-hi-v1
VAGOsolutions/SauerkrautLM-7b-v1-mistral
conversational
Eval Results
text-generation-inference
Inference Endpoints
Commit
•
a65f6d3
1
Parent(s):
692fa32
Adding Evaluation Results (#1)
Browse files- Adding Evaluation Results (a9226b1c8521558ee6b83a6ef03366024955f9f8)
Co-authored-by: Open LLM Leaderboard PR Bot <[email protected]>
README.md
CHANGED
@@ -11,6 +11,109 @@ tags:
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- OpenBuddy/openbuddy-zephyr-7b-v14.1
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- manishiitg/open-aditi-hi-v1
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- VAGOsolutions/SauerkrautLM-7b-v1-mistral
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---
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# Multilingual-mistral
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@@ -100,4 +203,17 @@ messages = [{"role": "user", "content": "Explain what a Mixture of Experts is in
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prompt = pipeline.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
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outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
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print(outputs[0]["generated_text"])
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-
```
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- OpenBuddy/openbuddy-zephyr-7b-v14.1
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- manishiitg/open-aditi-hi-v1
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- VAGOsolutions/SauerkrautLM-7b-v1-mistral
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model-index:
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- name: Multilingual-mistral
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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: 62.29
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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=gagan3012/Multilingual-mistral
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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: 81.76
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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=gagan3012/Multilingual-mistral
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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: 61.38
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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=gagan3012/Multilingual-mistral
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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: 55.53
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=gagan3012/Multilingual-mistral
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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: 75.53
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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=gagan3012/Multilingual-mistral
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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: 40.26
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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=gagan3012/Multilingual-mistral
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name: Open LLM Leaderboard
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---
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# Multilingual-mistral
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prompt = pipeline.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
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outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
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print(outputs[0]["generated_text"])
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```
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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_gagan3012__Multilingual-mistral)
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| Metric |Value|
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|---------------------------------|----:|
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|Avg. |62.79|
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|AI2 Reasoning Challenge (25-Shot)|62.29|
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|HellaSwag (10-Shot) |81.76|
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|MMLU (5-Shot) |61.38|
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|TruthfulQA (0-shot) |55.53|
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|Winogrande (5-shot) |75.53|
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|GSM8k (5-shot) |40.26|
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