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Model: richierich007/wingit-extractor-v1
Source: Original Platform

README.md

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+---
+license: apache-2.0
+language:
+- en
+pipeline_tag: text-generation
+tags:
+- unsloth
+- lora
+- sft
+- dpo
+- extraction
+- wingit
+---
+
+# WingIt Extractor v1
+
+## Model Description
+
+This is a specialized model for **extracting high-value dialogue, concepts, and principles from dating/pickup transcripts**.
+
+It was trained using:
+- **SFT**: 1,372 instruction examples (Prompt 3)
+- **DPO**: Preference optimization for correct classification
+
+## Use Cases
+
+- Extracting dialogues from raw transcripts
+- Identifying behavioral concepts (frame control, abundance, push-pull, etc.)
+- Classifying content as dialogue/concept/principle
+- Generating structured JSONL training data
+
+## Training Data
+
+- `Prompt 3_cleaned.jsonl`: 1,372 instruction examples
+- Base model: `unsloth/llama-3.1-8b-instruct-bnb-4bit`
+
+## Usage
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model = AutoModelForCausalLM.from_pretrained("richierich007/wingit-extractor-v1")
+tokenizer = AutoTokenizer.from_pretrained("richierich007/wingit-extractor-v1")
+
+prompt = "Extract dialogue and concepts from this transcript..."
+inputs = tokenizer(prompt, return_tensors="pt")
+outputs = model.generate(**inputs)
+print(tokenizer.decode(outputs[0]))