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README.md
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library_name: transformers
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---
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# Model Card for Model ID
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##
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### Model Description
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<!-- Provide a longer summary of what this model is. -->
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This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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- **Developed by:** [More Information Needed]
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- **Funded by [optional]:** [More Information Needed]
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- **Shared by [optional]:** [More Information Needed]
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- **Model type:** [More Information Needed]
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- **Language(s) (NLP):** [More Information Needed]
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- **License:** [More Information Needed]
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- **Finetuned from model [optional]:** [More Information Needed]
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### Model Sources [optional]
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<!-- Provide the basic links for the model. -->
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- **Repository:** [More Information Needed]
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- **Paper [optional]:** [More Information Needed]
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- **Demo [optional]:** [More Information Needed]
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[More Information Needed]
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## Bias, Risks, and Limitations
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[More Information Needed]
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### Recommendations
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<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
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## How to Get Started with the Model
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Use the code below to get started with the model.
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[More Information Needed]
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## Training Details
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### Training Data
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<!-- 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. -->
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[More Information Needed]
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### Training Procedure
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<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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#### Preprocessing [optional]
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[More Information Needed]
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#### Training Hyperparameters
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- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
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#### Speeds, Sizes, Times [optional]
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<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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[More Information Needed]
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## Evaluation
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<!-- This section describes the evaluation protocols and provides the results. -->
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### Testing Data, Factors & Metrics
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#### Testing Data
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<!-- This should link to a Dataset Card if possible. -->
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[More Information Needed]
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#### Factors
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<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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[More Information Needed]
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#### Metrics
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<!-- These are the evaluation metrics being used, ideally with a description of why. -->
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[More Information Needed]
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### Results
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[More Information Needed]
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#### Summary
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## Model Examination [optional]
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<!-- Relevant interpretability work for the model goes here -->
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[More Information Needed]
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## Environmental Impact
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<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
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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).
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- **Hardware Type:** [More Information Needed]
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- **Hours used:** [More Information Needed]
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- **Cloud Provider:** [More Information Needed]
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- **Compute Region:** [More Information Needed]
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- **Carbon Emitted:** [More Information Needed]
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## Technical Specifications [optional]
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### Model Architecture and Objective
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[More Information Needed]
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### Compute Infrastructure
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[More Information Needed]
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#### Hardware
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[More Information Needed]
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#### Software
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## Citation [optional]
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<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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**BibTeX:**
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[More Information Needed]
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**APA:**
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[More Information Needed]
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## Glossary [optional]
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##
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---
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language:
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- en
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- fr
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- de
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- es
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- it
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- pt
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- ru
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- zh
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- ja
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license: cc-by-nc-4.0
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library_name: transformers
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tags:
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- nsfw
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- Visual novel
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- roleplay
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- mergekit
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- merge
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base_model:
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- mistralai/Mistral-Small-Instruct-2407
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pipeline_tag: text-generation
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# Model Card for Model ID
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![image](./cover.png)
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Merged model using [mergekit](https://github.com/arcee-ai/mergekit/tree/main/mergekit)
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This model aimed to act like visual novel character.
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## Merge Format
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```yaml
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models:
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- model: mistralai/Mistral-Small-Instruct-2409_SFT
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layer_range: [0, 56]
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- model: mistralai/Mistral-Small-Instruct-2409
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layer_range: [0, 56]
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merge_method: slerp
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base_model: mistralai/Mistral-Small-Instruct-2409_SFT
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parameters:
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t:
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- filter: self_attn
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value: [0, 0.5, 0.3, 0.7, 1]
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- filter: mlp
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value: [1, 0.5, 0.7, 0.3, 0]
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- value: 0.5 # fallback for rest of tensors
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dtype: bfloat16
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```
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you have to resize chatwaifu and lucimaid's embedding size(131073 to 131072).
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# WaifuModel Collections
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- [TTS](https://huggingface.co/spow12/visual_novel_tts)
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- [Chat](https://huggingface.co/spow12/ChatWaifu_22B_v2.0)
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- [ASR](https://huggingface.co/spow12/Visual-novel-transcriptor)
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# Unified demo
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[WaifuAssistant](https://github.com/yw0nam/WaifuAssistant)
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# Update 2.0
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- 2024.09.23 Update 22B, Ver 2.0
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## Model Details
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### Model Description
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- **Developed by:** spow12(yw_nam)
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- **Shared by :** spow12(yw_nam)
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- **Model type:** CausalLM
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- **Language(s) (NLP):** japanese
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- **Finetuned from model :** [NeverSleep/Lumimaid-v0.2-12B](https://huggingface.co/NeverSleep/Lumimaid-v0.2-12B)
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Currently, chatbot has below personality.
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character | visual_novel |
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--- | --- |
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ムラサメ | Senren*Banka |
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茉子 | Senren*Banka |
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芳乃 | Senren*Banka |
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レナ | Senren*Banka |
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千咲 | Senren*Banka |
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芦花 | Senren*Banka |
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愛衣 | Café Stella and the Reaper's Butterflies |
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栞那 | Café Stella and the Reaper's Butterflies |
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ナツメ | Café Stella and the Reaper's Butterflies |
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希 | Café Stella and the Reaper's Butterflies |
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涼音 | Café Stella and the Reaper's Butterflies |
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あやせ | Riddle Joker |
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七海 | Riddle Joker |
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羽月 | Riddle Joker |
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茉優 | Riddle Joker |
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小春 | Riddle Joker |
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### Feature
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- Fluent Chat performance
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- Reduce repetition problem when generate with many turn(over 20~30)
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- Zero Shot character persona using description of character.
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- 128k context window
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- Memory ability that does not forget even after long-context generation
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## Demo
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You can use Demo in google colab.
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Check [Here](https://colab.research.google.com/drive/194_FN28reEPTwS51dwpLLBBwEfeoBjP9?usp=sharing)
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## Bias, Risks, and Limitations
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This model trained by japanese dataset included visual novel which contain nsfw content.
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So, The model may generate NSFW content.
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## Use & Credit
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This model is currently available for non-commercial & Research purpose only. Also, since I'm not detailed in licensing, I hope you use it responsibly.
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By sharing this model, I hope to contribute to the research efforts of our community (the open-source community and anime persons).
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This repository can use Visual novel-based RAG, but i will not distribute it yet because i'm not sure if it is permissible to release the data publicly.
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## Citation
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```bibtex
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@misc {ChatWaifu_22B_v2.0
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author = { YoungWoo Nam },
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title = { ChatWaifu_22B_v2.0 },
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year = 2024,
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url = { https://huggingface.co/spow12/ChatWaifu_22B_v2.0 },
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publisher = { Hugging Face }
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}
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```
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