Update README.md

README.md

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----
-base_model: MatteoKhan/Mistral-LLaMA-Fusion
-library_name: peft
----
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-# Model Card for Model ID
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-<!-- Provide a quick summary of what the model is/does. -->
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-
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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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-- **Shared by [optional]:** [More Information Needed]
-- **Model type:** [More Information Needed]
-- **Language(s) (NLP):** [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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-## 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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-### 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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-### 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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-## Bias, Risks, and Limitations
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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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-### Training Procedure
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-#### Preprocessing [optional]
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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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-## 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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-#### Factors
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-#### Metrics
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-### Results
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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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-## 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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-## Technical Specifications [optional]
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-### 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]
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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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-**APA:**
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-## Glossary [optional]
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-## More Information [optional]
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-## Model Card Authors [optional]
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-## Model Card Contact
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-### Framework versions
-
-- PEFT 0.15.2
+license: mit
+language:
+  - en
+base_model:
+  - MatteoKhan/Mistral-LLaMA-Fusion
+library_name: transformers
+tags:
+  - fine-tuned
+  - cosmetic-domain
+  - lora
+  - mistral
+  - llama
+  - rtx4060-optimized
+💄 Mistral-LLaMA-Fusion-Cosmetic: Expert Model for Beauty & Cosmetic Queries
+📌 Overview
+Mistral-LLaMA-Fusion-Cosmetic is a domain-specialized language model, fine-tuned on a dataset focused on cosmetic-related queries. Built from the powerful Mistral-LLaMA-Fusion, this version benefits from LoRA-based fine-tuning and GPU optimization on a RTX 4060.
+
+🔗 Created by: Matteo Khan
+🎓 Affiliation: Apprentice at TW3 Partners (Generative AI Research)
+📍 License: MIT
+
+🔗 Connect on LinkedIn
+🔍 Base Model
+
+🧠 Model Details
+Architecture: Mistral + LLaMA fusion
+
+Technique: Fine-tuned with LoRA (Low-Rank Adaptation)
+
+Base Model: MatteoKhan/Mistral-LLaMA-Fusion
+
+Training Dataset: Proprietary dataset (Parquet) of user queries in the cosmetic and beauty domain
+
+Training Hardware: RTX 4060 (8GB VRAM), 3 epochs
+
+🎯 Intended Use
+This model is optimized for:
+
+✅ Responding to beauty & cosmetic product questions
+
+✅ Assisting in cosmetic product recommendation
+
+✅ Enhancing chatbots in beauty domains
+
+✅ Cosmetic-focused creative content generation
+
+🛠️ Technical Details
+Fine-tuning Method: LoRA (r=8, α=16, dropout=0.05)
+
+Quantization: 4-bit NF4 via bitsandbytes
+
+Training Strategy: Gradient checkpointing + mixed precision (fp16)
+
+Sequence Length: 256 tokens
+
+Batch Strategy: Batch size 1 + gradient accumulation 16
+
+🧪 Training Configuration (LoRA)
+python
+Copier
+Modifier
+peft_config = LoraConfig(
+    task_type=TaskType.CAUSAL_LM,
+    inference_mode=False,
+    r=8,
+    lora_alpha=16,
+    lora_dropout=0.05,
+    target_modules=["q_proj", "v_proj", "k_proj", "o_proj", "gate_proj", "up_proj", "down_proj"],
+    bias="none",
+)
+🚀 How to Use
+python
+Copier
+Modifier
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_name = "MatteoKhan/mistral-llama-fusion-finetuned-cosmetic"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
+
+prompt = "What skincare products are best for oily skin?"
+inputs = tokenizer(prompt, return_tensors="pt")
+outputs = model.generate(**inputs, max_length=256)
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+⚠️ Limitations
+May hallucinate or provide incorrect information
+
+Knowledge is limited to cosmetic domain-specific data
+
+Should not replace professional dermatological advice
+
+🧾 Citation
+If you use this model in your research, please cite:
+
+bibtex
+Copier
+Modifier
+@misc{mistralllama2025cosmetic,
+  title={Mistral-LLaMA-Fusion-Cosmetic},
+  author={Matteo Khan},
+  year={2025},
+  note={Fine-tuned for cosmetic domain},
+  url={https://huggingface.co/MatteoKhan/mistral-llama-fusion-finetuned-cosmetic}
+}