Update README.md

README.md

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 ---
-base_model: mistralai/Mistral-7B-Instruct-v0.2
-library_name: peft
+language:
+- en
+tags:
+- mistral
+- lora
+- adapter
+- fine-tuned
+- politics
+- conversational
+license: mit
+datasets:
+- rohanrao/joe-biden-tweets
+- christianlillelund/joe-biden-2020-dnc-speech
 ---
 
-# Model Card for Model ID
-
-<!-- Provide a quick summary of what the model is/does. -->
-
+# Biden Mistral Adapter
 
+This is a LoRA adapter for the [Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) model, fine-tuned to emulate Joe Biden's distinctive speaking style, discourse patterns, and policy positions.
 
 ## Model Details
 
-### Model Description
-
-<!-- Provide a longer summary of what this model is. -->
-
-
-
-- **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. -->
-
-[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:** [More Information Needed]
-- **Hours used:** [More Information Needed]
-- **Cloud Provider:** [More Information Needed]
-- **Compute Region:** [More Information Needed]
-- **Carbon Emitted:** [More Information Needed]
-
-## Technical Specifications [optional]
-
-### Model Architecture and Objective
-
-[More Information Needed]
-
-### Compute Infrastructure
-
-[More Information Needed]
-
-#### Hardware
-
-[More Information Needed]
-
-#### Software
-
-[More Information Needed]
-
-## 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]
-## Training procedure
-
-The following `bitsandbytes` quantization config was used during training:
-- quant_method: bitsandbytes
-- load_in_8bit: False
-- load_in_4bit: True
-- llm_int8_threshold: 6.0
-- llm_int8_skip_modules: None
-- llm_int8_enable_fp32_cpu_offload: False
-- llm_int8_has_fp16_weight: False
-- bnb_4bit_quant_type: nf4
-- bnb_4bit_use_double_quant: True
-- bnb_4bit_compute_dtype: bfloat16
-
-### Framework versions
-
-- PEFT 0.7.0
+- **Base Model**: [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2)
+- **Model Type**: LoRA adapter (Low-Rank Adaptation)
+- **LoRA Rank**: 16
+- **Language**: English
+- **Training Focus**: Emulation of Joe Biden's communication style and response patterns
+
+## Intended Use
+
+This model is designed for:
+- Educational and research purposes related to political discourse and communication styles
+- Interactive simulations for understanding political rhetoric
+- Creative applications exploring political communication
+
+## Training Data
+
+This adapter was fine-tuned on two key datasets:
+- [Biden tweets dataset (2007-2020)](https://www.kaggle.com/datasets/rohanrao/joe-biden-tweets)
+- [Biden 2020 DNC speech dataset](https://www.kaggle.com/datasets/christianlillelund/joe-biden-2020-dnc-speech)
+
+These datasets were processed into an instruction format:
+
+## Training Procedure
+
+- **Framework**: Hugging Face Transformers and PEFT
+- **Optimization**: 4-bit quantization for memory efficiency
+- **LoRA Configuration**:
+  - `r=16`
+  - `lora_alpha=64`
+  - `lora_dropout=0.05`
+  - Target modules: q_proj, k_proj, v_proj, o_proj, gate_proj, up_proj, down_proj
+- **Training Parameters**:
+  - Batch size: 4
+  - Gradient accumulation steps: 4
+  - Learning rate: 2e-4
+  - Epochs: 3
+  - Learning rate scheduler: cosine
+  - Optimizer: paged_adamw_8bit
+  - BF16 precision
+
+## Limitations and Biases
+
+- The model is designed to mimic a speaking style and may not always provide factually accurate information
+- While it emulates Biden's rhetoric, it does not represent his actual views or statements
+- The model may reproduce biases present in the training data
+- Not suitable for production applications requiring factual accuracy without RAG enhancement
+
+## Usage
+
+This adapter should be applied to the Mistral-7B-Instruct-v0.2 base model:
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer, BitsAndBytesConfig
+from peft import PeftModel
+import torch
+
+# Load base model with 4-bit quantization
+base_model_id = "mistralai/Mistral-7B-Instruct-v0.2"
+bnb_config = BitsAndBytesConfig(
+    load_in_4bit=True,
+    bnb_4bit_compute_dtype=torch.float16,
+    bnb_4bit_quant_type="nf4",
+    bnb_4bit_use_double_quant=True,
+)
+
+# Load model and tokenizer
+model = AutoModelForCausalLM.from_pretrained(
+    base_model_id,
+    quantization_config=bnb_config,
+    device_map="auto", 
+    torch_dtype=torch.float16
+)
+tokenizer = AutoTokenizer.from_pretrained(base_model_id)
+
+# Apply the adapter
+model = PeftModel.from_pretrained(model, "nnat03/biden-mistral-adapter")
+
+# Generate a response
+prompt = "What's your vision for America's future?"
+input_text = f"<s>[INST] {prompt} [/INST]"
+inputs = tokenizer(input_text, return_tensors="pt").to("cuda")
+outputs = model.generate(**inputs, max_length=512, temperature=0.7, do_sample=True)
+response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+print(response.split("[/INST]")[-1].strip())
+```
+
+## Citation and Acknowledgments
+
+If you use this model in your research, please cite:
+
+@misc{nnat03-biden-mistral-adapter,
+author = {nnat03},
+title = {Biden Mistral Adapter},
+year = {2023},
+publisher = {Hugging Face},
+howpublished = {\url{https://huggingface.co/nnat03/biden-mistral-adapter}}
+}
+
+
+## Ethical Considerations
+
+This model is created for educational and research purposes. It attempts to mimic the speaking style of a public figure but does not represent their actual views or statements. Use responsibly.