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## Model Details
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### Model Description
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<!-- Provide a longer summary of what this model is. -->
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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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## Uses
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<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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### Direct Use
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<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
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[More Information Needed]
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### Downstream Use [optional]
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<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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[More Information Needed]
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### Out-of-Scope Use
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<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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[More Information Needed]
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## Bias, Risks, and Limitations
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<!-- This section is meant to convey both technical and sociotechnical 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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[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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#### Software
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## Citation [optional]
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---
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license: apache-2.0
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tags:
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- mistral
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- Uncensored
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- text-generation-inference
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- transformers
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- unsloth
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- trl
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- roleplay
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- conversational
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- rp
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datasets:
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- N-Bot-Int/Iris-Uncensored-R1
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- N-Bot-Int/Moshpit-Combined-R2-Uncensored
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- N-Bot-Int/Mushed-Dataset-Uncensored
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- N-Bot-Int/Muncher-R1-Uncensored
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- unalignment/toxic-dpo-v0.2
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language:
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- en
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base_model:
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- unsloth/mistral-7b-instruct-v0.3-bnb-4bit
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pipeline_tag: text-generation
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library_name: transformers
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metrics:
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- character
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---
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# Official Quants are Uploaded By Us
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- [MistThena7BV2-GGUF](https://huggingface.co/N-Bot-Int/MistThena7BV2-GGUF)
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# Support us on Ko-Fi!
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- [](https://ko-fi.com/J3J61D8NHV)
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# MistThena7B - V2.
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- Introducing our Mindboggling MistThena7B **V2**, This Version Offer an Upgraded RP experience, beyond Other AI model
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We've made, Outcompetting our 3B, 1B, MythoMax, Deepseek and Hermes for Roleplaying!
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- **MistThena7B-V2** Offer an expanded Roleplay capabilities, using our EmojiEmulsifyer Program to Train MistThena7B
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To Use Emojis, expanding the Roleplaying Immersiveness and Actionsets MistThena7B can do!
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- Activate MistThena's Expanded Actions, by mirroring it(ie using Emoji on your own prompts), to ensure MistThena's
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Use of Emoji or Actions!
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- MistThena7B contains more Fine-tuned Dataset so please Report any issues found through our email
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[nexus.networkinteractives@gmail.com](mailto:nexus.networkinteractives@gmail.com)
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about any overfitting, or improvements for the future Model **V3**,
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Once again feel free to Modify the LORA to your likings, However please consider Adding this Page
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for credits and if you'll increase its **Dataset**, then please handle it with care and ethical considerations
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- MistThena is
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- **Developed by:** N-Bot-Int
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- **License:** apache-2.0
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- **Finetuned from model:** unsloth/mistral-7b-instruct-v0.3-bnb-4bit
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- **Sequential Trained from Model:** N-Bot-Int/OpenElla3-Llama3.2A
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- **Dataset Combined Using:** Mosher-R1(Propietary Software)
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- Comparison Metric Score
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- Metrics Made By **ItsMeDevRoland**
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Which compares:
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- **MistThena7B-V1**
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- **MistThena7B-V2 : 60 STEP VERSION**
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Which are All Ranked with the Same Prompt, Same Temperature, Same Hardware(Google Colab),
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To Properly Showcase the differences and strength of the Models
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---
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# 🌀 MistThema-7B V2: Slower Beats, Stronger Bonds — A Roleplay Revival
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> "She may not win the speed race, but when it comes to presence and performance — she owns the stage."
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---
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# MistThema-7B V2 isn’t just an upgrade — she’s a reinvention. Built on V1’s storytelling roots, V2 shifts her focus inward: longer scenes, deeper characters, and dialogue that breathes.
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- 💬 **Roleplay Evaluation**
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- ✍️ **Length Score**: 0.34 → **1.00** (🚀)
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- 🧠 **Character Consistency**: 0.20 → **0.53**
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- 🌌 **Immersion**: 0.00 → **0.47**
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- 🎭 **Overall RP Score**: 0.17 → **0.67**
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> She no longer just responds — she *inhabits*. MistThema-7B V2 is the method actor of models, channeling roles with vivid coherence and creative depth.
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---
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# ⚙️ The Cost of Craft: Time for Thought
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- 🕒 **Inference Time**: 114s → **179s** (↑)
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- ⚡ **Tokens/sec**: 1.51 → **1.28** (↓)
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> Yes, she’s slower — but that’s not a bug. That’s intention. Every word is more considered, every output more deliberate.
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---
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# 📏 Traditional Metrics? A Trade-off
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- 📘 **BLEU Score**: 0.43 → **0.18**
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- 📕 **ROUGE-L**: 0.60 → **0.32**
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> While V1 outperforms on surface-level matching, V2 is optimized for *experiential fidelity*, not rigid overlap.
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---
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# 🎯 Reimagined for Realness
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MistThema-7B V2 isn’t trying to mimic — she’s trying to *immerse*. Designed to tell stories, embody roles, and hold character in long-form exchanges.
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- 🧩 Tailored for:
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- Narrative-heavy use cases
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- Emotional continuity and consistency
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- Richer, longer interactions
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---
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> “MistThema-7B V2 trades benchmarks for believability. Less about matching — more about meaning. Less polished — more *present*.”
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# MistThema-7B V2 is where slower feels *stronger*.
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---
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| 114 |
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- # Notice
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- **For a Good Experience, Please use**
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| 116 |
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- Low temperature 1.5, min_p = 0.1 and max_new_tokens = 128
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- # Detail card:
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- Parameter
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- 7 Billion Parameters
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- (Please visit your GPU Vendor if you can Run 7B models)
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| 123 |
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| 124 |
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- Training
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| 125 |
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- 250 Steps
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| 126 |
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- N-Bot-Int/Iris_Uncensored_R2
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| 127 |
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- 60 Steps
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| 128 |
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- N-Bot-Int/Millie_DPO
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| 129 |
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| 130 |
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- Finetuning tool:
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- Unsloth AI
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- This mistral model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
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[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
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- Fine-tuned Using:
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- Google Colab
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