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-library_name: transformers
 tags:
 - unsloth
-- trl
-- sft
 ---
-# Model Card for Model ID
-<!-- Provide a quick summary of what the model is/does. -->
-## Model Details
-### Model Description
-<!-- Provide a longer summary of what this model is. -->
-This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
-- **Developed by:** [More Information Needed]
-- **Funded by [optional]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
-- **Model type:** [More Information Needed]
-- **Language(s) (NLP):** [More Information Needed]
-- **License:** [More Information Needed]
-- **Finetuned from model [optional]:** [More Information Needed]
-### Model Sources [optional]
-<!-- Provide the basic links for the model. -->
-- **Repository:** [More Information Needed]
-- **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. -->
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-### Downstream Use [optional]
-<!-- 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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-### Out-of-Scope Use
-<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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-## Bias, Risks, and Limitations
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-### 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. -->
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-### 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]
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-#### 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]
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-## Evaluation
-<!-- This section describes the evaluation protocols and provides the results. -->
-### Testing Data, Factors & Metrics
-#### Testing Data
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-#### Factors
-<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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-#### Metrics
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-### Results
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-#### Summary
-## Model Examination [optional]
-<!-- Relevant interpretability work for the model goes here -->
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-## 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:** [More Information Needed]
-- **Hours used:** [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]
-<!-- 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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-## Glossary [optional]
-<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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-## More Information [optional]
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-## Model Card Authors [optional]
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 ---
+base_model: meta-llama/Llama-3.2-3B-Instruct
 tags:
+- text-generation-inference
+- transformers
 - unsloth
+- llama
+- gguf
+- alphaaico
+- relationship-ai
+- husband-helper
+- communication
+- humor
+license: apache-2.0
+language:
+- en
 ---
+<div align="center">
+<img src="https://cdn-uploads.huggingface.co/production/uploads/669777597cb32718c20d97e9/4emWK_PB-RrifIbrCUjE8.png"
+     alt="Title card"
+     style="width: 500px;
+            height: auto;
+            object-position: center top;">
+</div>
+# Uploaded Model
+- **Developed by:** Alpha AI
+- **License:** apache-2.0
+- **Finetuned from model:** meta-llama/Llama-3.2-3B-Instruct
+This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Hugging Face's TRL library.
+## OopsHusBot-3B: The AI Model for Husbands Who Try (and Sometimes Fail) at Communication
+### Overview
+Husbands mean well. Really. But communication can sometimes feel like an unsolvable puzzle. OopsHusBot-3B is here to help! Designed to assist husbands in navigating tricky conversations, avoiding misunderstandings, and delivering just the right amount of romance (without overdoing it), this model is your ultimate survival guide for relationship communication.
+Built on meta-llama/Llama-3.2-3B-Instruct, this model is fine-tuned to prevent classic communication blunders—because sometimes, a simple “OK” isn’t the right answer.
+### Model Details
+- **Base Model:** meta-llama/Llama-3.2-3B-Instruct
+- **Fine-tuned By:** Alpha AI
+- **Training Framework:** Unsloth
+#### Quantization Levels Available
+- q4_k_m
+- q5_k_m
+- q8_0
+- 16-bit (this, full precision) - [Link](https://huggingface.co/alphaaico/OopsHusBot-3B)
+*(Note: The INT1 16-bit link is referenced (https://huggingface.co/alphaaico/OopsHusBot-3B)*
+**Format:** GGUF (Optimized for local deployments, https://huggingface.co/alphaaico/OopsHusBot-3B-GGUF)
+### Key Features
+- **Auto-Smooth Talk** – Helps generate heartfelt, thoughtful responses without sounding robotic.
+- **Oops Recovery Mode** – Immediate damage control when you say something unintentionally dumb.
+- **Danger Phrase Decoder** – Correctly interprets high-risk phrases like “Do whatever you want” (Hint: She doesn’t mean that).
+- **Anniversary & Birthday Reminder** – Generates sweet, meaningful texts to keep you in the clear.
+- **Pre-Apology Generator** – Because sometimes, you don’t know what you did wrong—but you know you need to fix it.
+- **Selective Hearing Fixer** – Crafts responses to make it seem like you were totally paying attention.
+### Training & Data
+**OopsHusBot-3B** has been trained on a carefully curated dataset of:
+- Romantic yet slightly clueless husband responses
+- Apology best practices (ranked by effectiveness)
+- Deciphering “I’m fine” and other cryptic messages
+- Emergency sweet talk for when things go south
+- When to text “I love you” without being asked
+- Avoiding the classic “Are you mad?” trap
+### Important Warnings
+❌ Not responsible for husbands who still say “Calm down.”
+❌ Does not fix situations where you actually forgot her birthday.
+❌ AI-generated compliments may be too good, causing suspicion.
+❌ Disables “I told you so” responses for your safety.
+### Use Cases
+- **When she says “I have nothing to wear”** – Generates supportive yet non-argumentative responses.
+- **Emergency Romance Mode** – For those “You never say nice things to me” situations.
+- **Silent Treatment Prevention** – Helps craft messages to de-escalate tension before it spirals.
+- **Reading Between the Lines** – Ensures you don’t misinterpret “Do whatever you want.”
+- **Gift Idea Generator** – Ensures you never make the mistake of buying a vacuum as a romantic gift again.
+### Model Performance
+**OopsHusBot-3B** has been further optimized to deliver:
+- **Empathic and Context-Aware Responses** – Improved understanding of user inputs with a focus on empathetic replies.
+- **High Efficiency on Consumer Hardware** – Maintains quick inference speeds even with more advanced conversation modeling.
+- **Balanced Coherence and Creativity** – Strikes an ideal balance for real-world dialogue applications, allowing for both coherent answers and creative flair.
+### Limitations & Biases
+Like any AI system, this model may exhibit biases stemming from its training data. Users should employ it responsibly and consider additional fine-tuning if needed for sensitive or specialized applications.
+### License
+Released under the **Apache-2.0** license. For full details, please consult the license file in the Hugging Face repository.
+### Acknowledgments
+Special thanks to the Unsloth team for their optimized training pipeline for LLaMA models. Additional appreciation goes to Hugging Face’s TRL library for enabling accelerated and efficient fine-tuning workflows.
+### NOTE - If you’re a husband who means well but sometimes just doesn’t get it—OopsHusBot-3B has your back. 🚀🔥