---
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

<!-- Provide a quick summary of what the model is/does. -->

This modelcard aims to be a base template for new models. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/modelcard_template.md?plain=1).

### VQV1

### USED FOR PERSONAL ONLY 

<!-- Provide a longer summary of what this model is. -->



- **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]

<!-- Provide the basic links for the model. -->

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

## Uses

<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->

### Direct Use

<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->

[More Information Needed]

### Downstream Use [optional]

<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->

[More Information Needed]

### Out-of-Scope Use

<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->

[More Information Needed]

## Bias, Risks, and Limitations

<!-- This section is meant to convey both technical and sociotechnical limitations. -->

[More Information Needed]

### Recommendations

<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->

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

<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->

[More Information Needed]

### Training Procedure

<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->

#### Preprocessing [optional]

[More Information Needed]


#### Training Hyperparameters

- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->

#### Speeds, Sizes, Times [optional]

<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->

[More Information Needed]

## Evaluation

<!-- This section describes the evaluation protocols and provides the results. -->

### Testing Data, Factors & Metrics

#### Testing Data

<!-- This should link to a Dataset Card if possible. -->

[More Information Needed]

#### Factors

<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->

[More Information Needed]

#### Metrics

<!-- These are the evaluation metrics being used, ideally with a description of why. -->

[More Information Needed]

### Results

[More Information Needed]

#### Summary



## Model Examination [optional]

<!-- Relevant interpretability work for the model goes here -->

[More Information Needed]

## Environmental Impact

<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->

Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).

- **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]

<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->

**BibTeX:**

[More Information Needed]

**APA:**

[More Information Needed]

## Glossary [optional]

<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->

[More Information Needed]

## More Information [optional]

[More Information Needed]

## Model Card Authors [optional]

[More Information Needed]

## Model Card Contact

[More Information Needed]