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metadata
license: apache-2.0
datasets:
  - open-thoughts/OpenThoughts-114k
  - fka/awesome-chatgpt-prompts
  - open-r1/OpenR1-Math-220k
  - Congliu/Chinese-DeepSeek-R1-Distill-data-110k
  - Congliu/Chinese-DeepSeek-R1-Distill-data-110k-SFT
  - FreedomIntelligence/medical-o1-reasoning-SFT
  - saiyan-world/Goku-MovieGenBench
  - cais/hle
  - ServiceNow-AI/R1-Distill-SFT
  - cognitivecomputations/dolphin-r1
language:
  - en
  - hi
  - as
  - mr
  - uk
  - ja
  - aa
  - ab
  - ae
  - ak
  - am
  - af
  - ar
  - av
  - ay
  - az
  - ba
  - bg
  - be
metrics:
  - accuracy
  - bertscore
  - bleu
  - code_eval
base_model:
  - deepseek-ai/DeepSeek-V3
  - deepseek-ai/DeepSeek-R1
  - deepseek-ai/DeepSeek-R1-Distill-Qwen-32B
  - mistralai/Mistral-Small-24B-Instruct-2501
library_name: diffusers

Model Card for Model ID

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

VQV1

USED FOR PERSONAL ONLY

  • Developed by: [YuRiVeRTi]:
  • Funded by [YuRiVeRTi]:
  • Shared by [YuRiVeRTi]: [DEVELOP BY YURIVERTI FOR FINETUNE VR WITH UNCENSORED CAN RUN LOCALLY ON THE COMMAND]
  • Model type: [VQV1]
  • Language(s) (NLP): [Ml.LLM]
  • License: [ALPHACT 2.0]
  • Finetuned from model : [VQV1 RUNS ON V3 MODLE ]

Model Sources [optional]

  • Repository: []
  • open-thoughts/OpenThoughts-114k
  • Paper [optional]: [More Information Needed]
  • Demo [optional]: [More Information Needed]

Uses

Direct Use

[More Information Needed]

Downstream Use [optional]

[More Information Needed]

Out-of-Scope Use

[More Information Needed]

Bias, Risks, and Limitations

[More Information Needed]

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.

[More Information Needed]

Training Details

Training Data

[More Information Needed]

Training Procedure

Preprocessing [optional]

[More Information Needed]

Training Hyperparameters

  • Training regime: [More Information Needed]

Speeds, Sizes, Times [optional]

[More Information Needed]

Evaluation

Testing Data, Factors & Metrics

Testing Data

[More Information Needed]

Factors

[More Information Needed]

Metrics

[More Information Needed]

Results

[More Information Needed]

Summary

Model Examination [optional]

[More Information Needed]

Environmental Impact

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

  • Hardware Type: [RTX 5090 Ti]
  • Hours used: [2160 hours]
  • Cloud Provider: [CLOUDFARE & GITHUB'HUGGING FACE]
  • Compute Region: [More Information Needed]
  • Carbon Emitted: [500 kg of CO2 ]

Technical Specifications [optional]

Model Architecture and Objective

[More Information Needed]

Compute Infrastructure

[More Information Needed]

Hardware

[RTX 5090 Ti]

Software

[ORACAL.LINUX.LINUX ARCH]

Citation [optional]

BibTeX:

[More Information Needed]

APA:

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Glossary [optional]

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More Information [optional]

[More Information Needed]

Model Card Authors [optional]

[More Information Needed]

Model Card Contact

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