210 lines
6.6 KiB
Markdown
210 lines
6.6 KiB
Markdown
---
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language:
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- en
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license: apache-2.0
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tags:
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- text-generation
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datasets:
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- THUDM/webglm-qa
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- databricks/databricks-dolly-15k
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- cognitivecomputations/wizard_vicuna_70k_unfiltered
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- totally-not-an-llm/EverythingLM-data-V3
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- Amod/mental_health_counseling_conversations
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- sablo/oasst2_curated
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- starfishmedical/webGPT_x_dolly
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- Open-Orca/OpenOrca
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- mlabonne/chatml_dpo_pairs
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base_model: JackFram/llama-68m
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widget:
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- messages:
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- role: system
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content: You are a career counselor. The user will provide you with an individual
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looking for guidance in their professional life, and your task is to assist
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them in determining what careers they are most suited for based on their skills,
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interests, and experience. You should also conduct research into the various
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options available, explain the job market trends in different industries, and
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advice on which qualifications would be beneficial for pursuing particular fields.
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- role: user
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content: Heya!
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- role: assistant
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content: Hi! How may I help you?
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- role: user
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content: I am interested in developing a career in software engineering. What
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would you recommend me to do?
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- messages:
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- role: system
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content: You are a knowledgeable assistant. Help the user as much as you can.
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- role: user
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content: How to become healthier?
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- messages:
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- role: system
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content: You are a helpful assistant who provides concise responses.
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- role: user
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content: Hi!
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- role: assistant
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content: Hello there! How may I help you?
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- role: user
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content: I need to build a simple website. Where should I start learning about web development?
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- messages:
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- role: system
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content: You are a very creative assistant. User will give you a task, which you should complete with all your knowledge.
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- role: user
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content: Write the background story of an RPG game about wizards and dragons in a sci-fi world.
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inference:
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parameters:
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max_new_tokens: 64
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penalty_alpha: 0.5
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top_k: 4
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model-index:
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- name: Llama-68M-Chat-v1
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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: 23.29
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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=Felladrin/Llama-68M-Chat-v1
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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: 28.27
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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=Felladrin/Llama-68M-Chat-v1
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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: 25.18
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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=Felladrin/Llama-68M-Chat-v1
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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: 47.27
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Felladrin/Llama-68M-Chat-v1
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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: 54.3
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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=Felladrin/Llama-68M-Chat-v1
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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: 0.0
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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=Felladrin/Llama-68M-Chat-v1
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name: Open LLM Leaderboard
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---
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# A Llama Chat Model of 68M Parameters
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- Base model: [JackFram/llama-68m](https://huggingface.co/JackFram/llama-68m)
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- Datasets:
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- [THUDM/webglm-qa](https://huggingface.co/datasets/THUDM/webglm-qa)
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- [databricks/databricks-dolly-15k](https://huggingface.co/datasets/databricks/databricks-dolly-15k)
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- [cognitivecomputations/wizard_vicuna_70k_unfiltered](https://huggingface.co/datasets/cognitivecomputations/wizard_vicuna_70k_unfiltered)
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- [totally-not-an-llm/EverythingLM-data-V3](https://huggingface.co/datasets/totally-not-an-llm/EverythingLM-data-V3)
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- [Amod/mental_health_counseling_conversations](https://huggingface.co/datasets/Amod/mental_health_counseling_conversations)
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- [sablo/oasst2_curated](https://huggingface.co/datasets/sablo/oasst2_curated)
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- [starfishmedical/webGPT_x_dolly](https://huggingface.co/datasets/starfishmedical/webGPT_x_dolly)
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- [Open-Orca/OpenOrca](https://huggingface.co/datasets/Open-Orca/OpenOrca)
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- [mlabonne/chatml_dpo_pairs](https://huggingface.co/datasets/mlabonne/chatml_dpo_pairs)
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- Availability in other ML formats:
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- GGUF: [afrideva/Llama-68M-Chat-v1-GGUF](https://huggingface.co/afrideva/Llama-68M-Chat-v1-GGUF)
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- ONNX: [Felladrin/onnx-Llama-68M-Chat-v1](https://huggingface.co/Felladrin/onnx-Llama-68M-Chat-v1)
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## Recommended Prompt Format
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```
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<|im_start|>system
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{system_message}<|im_end|>
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<|im_start|>user
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{user_message}<|im_end|>
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<|im_start|>assistant
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```
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## Recommended Inference Parameters
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```yml
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penalty_alpha: 0.5
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top_k: 4
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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_Felladrin__Llama-68M-Chat-v1)
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| Metric |Value|
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|---------------------------------|----:|
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|Avg. |29.72|
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|AI2 Reasoning Challenge (25-Shot)|23.29|
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|HellaSwag (10-Shot) |28.27|
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|MMLU (5-Shot) |25.18|
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|TruthfulQA (0-shot) |47.27|
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|Winogrande (5-shot) |54.30|
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|GSM8k (5-shot) | 0.00|
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