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Model: justinthelaw/Qwen2.5-0.5B-Instruct-Resume-Cover-Letter-SFT Source: Original Platform
2026-06-01 00:47:18 +08:00
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+---
+license: apache-2.0
+language:
+  - en
+library_name: transformers
+tags:
+  - qwen2.5
+  - onnx
+  - transformers.js
+  - text-generation
+  - fine-tuned
+  - sft
+  - lora
+  - resume
+  - chatbot
+base_model: "Qwen/Qwen2.5-0.5B-Instruct"
+datasets:
+  - "justinthelaw/Resume-Cover-Letter-SFT-Dataset"
+pipeline_tag: text-generation
+---
+
+# justinthelaw/Qwen2.5-0.5B-Instruct-Resume-Cover-Letter-SFT
+
+A fine-tuned version of [Qwen/Qwen2.5-0.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-0.5B-Instruct) trained with an SFT + LoRA pipeline to answer questions about **Justin**'s professional background, skills, and experience.
+
+## Model Description
+
+This model is designed for browser-based inference using [transformers.js](https://huggingface.co/docs/transformers.js). It powers a personal website chatbot that can answer questions about Justin's resume, work experience, education, and skills.
+
+### Training Pipeline
+
+The model is trained using **SFT (Supervised Fine-Tuning)** with **LoRA adapters**, where factual memorization is enforced via conversation-formatted QA pairs.
+
+### Training Details
+
+- **Base Model**: [Qwen/Qwen2.5-0.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-0.5B-Instruct)
+- **Training Dataset**: [justinthelaw/Resume-Cover-Letter-SFT-Dataset](https://huggingface.co/datasets/justinthelaw/Resume-Cover-Letter-SFT-Dataset)
+- **LoRA Configuration**:
+  - Rank (r): 64
+  - Alpha: 128
+  - Dropout: 0.05
+  - Target Modules: q_proj, k_proj, v_proj, o_proj, gate_proj, up_proj, down_proj
+
+#### SFT Training Configuration
+
+- Epochs: 8
+- Batch Size: 16
+- Learning Rate: 2e-05
+
+## Model Formats
+
+This repository contains multiple model formats:
+
+| Format      | Location   | Use Case                                                  |
+| ----------- | ---------- | --------------------------------------------------------- |
+| SafeTensors | `/` (root) | Python/PyTorch inference                                  |
+| ONNX        | `/onnx/`   | FP32 + quantized weights for ONNX Runtime/Web inference   |
+
+## Usage
+
+### Browser (transformers.js)
+
+```javascript
+import { pipeline } from "@huggingface/transformers";
+
+const generator = await pipeline("text-generation", "justinthelaw/Qwen2.5-0.5B-Instruct-Resume-Cover-Letter-SFT", {
+  dtype: "fp32",
+});
+
+const output = await generator("What is Justin's background?", {
+  max_new_tokens: 256,
+});
+```
+
+### Python (Transformers)
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model = AutoModelForCausalLM.from_pretrained("justinthelaw/Qwen2.5-0.5B-Instruct-Resume-Cover-Letter-SFT")
+tokenizer = AutoTokenizer.from_pretrained("justinthelaw/Qwen2.5-0.5B-Instruct-Resume-Cover-Letter-SFT")
+
+prompt = "What is Justin's background?"
+inputs = tokenizer(prompt, return_tensors="pt")
+outputs = model.generate(**inputs, max_new_tokens=256)
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+```
+
+## Intended Use
+
+This model is intended for:
+
+- Personal website chatbots
+- Resume Q&A applications
+- Demonstrating fine-tuning techniques for personalized AI assistants
+
+## Limitations
+
+- The model is specifically trained on Justin's resume and may not generalize to other topics
+- Responses are based on training data and may not reflect real-time information
+- Not suitable for general-purpose question answering
+
+## Author
+
+### Justin
+
+- GitHub: [justinthelaw](https://github.com/justinthelaw)
+- HuggingFace: [justinthelaw](https://huggingface.co/justinthelaw)
+
+## License
+
+This model is released under the Apache 2.0 license.