AiJoker
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openchat_3.5-slp-jordan-belfort

@@ -3,201 +3,82 @@ library_name: transformers
 tags:
 - trl
 - sft
 ---
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 tags:
 - trl
 - sft
+- qna
+- jordan-belfort
+- sales
+- mindset
+- persuasion
+base_model:
+- openchat/openchat_3.5
+pipeline_tag: text-generation
 ---
+# Model Card for Jordan Belfort Q&A Model
+This model is a fine-tuned version of a transformer-based language model trained using supervised fine-tuning (SFT) on a custom Q&A dataset derived from Jordan Belfort's book. The model is optimized to answer questions related to the book's content, including topics like sales, persuasion, mindset, and personal development strategies.
+---
 ## Model Details
+- **Developed by:** Jobix.ai
+- **Finetuned from model:** `openchat 3.5*
+- **Language(s):** English
+- **Model type:** Q&A / Instruction-following
+- **License:** apache-2.0 *(or your chosen license)*
+---
+## Model Sources
+- **Training Data:** Custom Q&A dataset built from the full content of Jordan Belfort’s book.
+- **Method:** Supervised fine-tuning (TRL + SFT)
+---
 ## Uses
 ### Direct Use
+- Ask specific questions about concepts, strategies, and advice in Jordan Belfort's book.
+- Get summaries of chapters, sales techniques, or mindset frameworks presented in the book.
+- Useful for salespeople, coaches, or individuals studying persuasion and personal development.
 ### Out-of-Scope Use
+- Not trained for general-purpose Q&A outside the context of the book.
+- Not suitable for legal, financial, or medical advice.
+---
 ## Training Details
+### Training Procedure
+- **Trainer:** `trl.SFTTrainer`
+- **Precision:** bfloat16
+- **Epochs:** 7
+- **Optimizer:** AdamW
+- **LR Scheduler:** Cosine with warmup
+- **Loss:** CrossEntropyLoss on prompt-response pairs
+### Dataset
+- Approx. ~2,000 curated Q&A pairs covering all chapters and sections of the book.
+- Balanced across concepts like tonality, straight-line persuasion, mindset, sales process, and personal stories.
+---
 ## Evaluation
+- Manual evaluation on question coverage and accuracy.
+- Model shows strong performance in recalling specific ideas and quoting relevant sections.
+---
+## Example Usage
+```python
+from transformers import pipeline
+qa = pipeline("text-generation", model="your-username/jordan-belfort-qa")
+prompt = "What is the straight-line sales method according to Jordan Belfort?"
+response = qa(prompt, max_new_tokens=200, do_sample=False)
+print(response[0]["generated_text"])