Luna-Samantha / README.md
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metadata
license: apache-2.0
datasets:
  - HuggingFaceFW/fineweb
  - nvidia/ChatQA-Training-Data
  - allenai/WildChat-1M
  - TIGER-Lab/MMLU-Pro
  - H-D-T/Buzz
  - PleIAs/Post-OCR-Correction
  - mlabonne/orpo-dpo-mix-40k
  - m-a-p/Matrix
  - satellogic/EarthView
language:
  - en
  - fr
  - es
metrics:
  - accuracy
  - bertscore
  - bleu
  - brier_score
  - cer
  - character
  - charcut_mt
  - chrf
  - code_eval
library_name: adapter-transformers
tags:
  - code
  - art
  - finance
  - text-generation-inference
  - merge

Model Card for Model ID


model-index: - name: Yi-34B results: - task: type: text-generation dataset: name: ai2_arc type: ai2_arc metrics: - name: AI2 Reasoning Challenge (25-Shot) type: AI2 Reasoning Challenge (25-Shot) value: 64.59 source: name: Open LLM Leaderboard url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard

GIT_LFS_SKIP_SMUDGE=1 git clone git@hf.co:spaces/dalle-mini/dalle-mini

GIT_LFS_SKIP_SMUDGE=1 git clone https://huggingface.co/openbmb/MiniCPM-Llama3-V-2_5

GIT_LFS_SKIP_SMUDGE=1 git clone https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct

https://gist.github.com/f2acd35a005b3f88893ecb04c975eaa6.git

This modelcard aims to be a base template for new models. It has been generated using this raw template.

Model Details

Model Description

  • Developed by: [More Information Needed]
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  • Model type: [More Information Needed]
  • Language(s) (NLP): [More Information Needed]
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  • Finetuned from model [optional]: [More Information Needed]

Model Sources [optional]

  • Repository: [More Information Needed]
  • Paper [optional]: [More Information Needed]
  • Demo [optional]: [More Information Needed]

Uses

Direct Use

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Downstream Use [optional]

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Out-of-Scope Use

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Bias, Risks, and Limitations

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Recommendations

Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.

How to Get Started with the Model

Use the code below to get started with the model.

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Training Details

Training Data

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Training Procedure

Preprocessing [optional]

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Training Hyperparameters

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Speeds, Sizes, Times [optional]

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Evaluation

Testing Data, Factors & Metrics

Testing Data

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Factors

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Metrics

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Results

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Summary

Model Examination [optional]

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Environmental Impact

Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).

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  • Hours used: [More Information Needed]
  • Cloud Provider: [More Information Needed]
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  • Carbon Emitted: [More Information Needed]

Technical Specifications [optional]

Model Architecture and Objective

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Compute Infrastructure

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Hardware

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Software

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Citation [optional]

BibTeX:

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APA:

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Glossary [optional]

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Model Card Authors [optional]

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Model Card Contact

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