Upload folder using huggingface_hub

README.md

@@ -1,122 +1,202 @@
 ---
-language:
-- en
-tags:
-- mistral
-- lora
-- adapter
-- fine-tuned
-- politics
-- conversational
-license: mit
-datasets:
-- pookie3000/trump-interviews
-- bananabot/TrumpSpeeches
+base_model: mistralai/Mistral-7B-Instruct-v0.2
+library_name: peft
 ---
 
-# Trump Mistral Adapter
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
 
-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 Donald Trump's distinctive speaking style, discourse patterns, and policy positions.
 
 ## Model Details
 
-- **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 Donald Trump'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:
-- [Trump interviews dataset](https://huggingface.co/datasets/pookie3000/trump-interviews)
-- [Trump speeches dataset](https://huggingface.co/datasets/bananabot/TrumpSpeeches)
-
-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 Trump'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/trump-mistral-adapter")
-
-# Generate a response
-prompt = "What's your plan for border security?"
-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-trump-mistral-adapter,
-author = {nnat03},
-title = {Trump Mistral Adapter},
-year = {2023},
-publisher = {Hugging Face},
-howpublished = {\url{https://huggingface.co/nnat03/trump-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.
+### 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]
+### Framework versions
+
+- PEFT 0.15.0

adapter_config.json

@@ -3,6 +3,7 @@
   "auto_mapping": null,
   "base_model_name_or_path": "mistralai/Mistral-7B-Instruct-v0.2",
   "bias": "none",
+  "corda_config": null,
   "eva_config": null,
   "exclude_modules": null,
   "fan_in_fan_out": false,
@@ -23,15 +24,21 @@
   "rank_pattern": {},
   "revision": null,
   "target_modules": [
+    "o_proj",
     "k_proj",
+    "gate_proj",
+    "q_proj",
     "down_proj",
     "v_proj",
-    "o_proj",
-    "gate_proj",
-    "up_proj",
-    "q_proj"
+    "up_proj"
   ],
   "task_type": "CAUSAL_LM",
+  "trainable_token_indices": null,
   "use_dora": false,
-  "use_rslora": false
+  "use_rslora": false,
+  "description": "Merged adapter combining style and identity LoRA weights",
+  "source_adapters": [
+    "nnat03/trump-mistral-adapter",
+    "./identity-adapters/trump-identity-adapter"
+  ]
 }

adapter_model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:f3ac3a4bf74d6b7baf6aaacd04b764953e45187281d5841bdf1d34b5f384429a
+oid sha256:86f9a993cbceb9f29ff22d1cdc15d09e8c906a3f27d694d5037968afa8c12278
 size 167832240