| --- |
| base_model: deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B |
| library_name: peft |
| pipeline_tag: text-generation |
| language: en |
| tags: |
| - deepseek |
| - text-generation |
| - conversational |
| --- |
| |
| # Microsoft 365 Data Management Expert |
|
|
| This model is fine-tuned from deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B for answering questions about Microsoft 365 data management, |
| specifically focusing on SharePoint, OneDrive, and Teams. It provides detailed responses about: |
|
|
| - Data governance |
| - Retention policies |
| - Permissions management |
| - Version control |
| - Sensitivity labels |
| - Document lifecycle |
| - Compliance features |
| - And more |
|
|
| ## Model Details |
|
|
| - **Base Model**: deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B |
| - **Training**: Fine-tuned using LoRA |
| - **Task**: Question-answering about Microsoft 365 data management |
| - **Language**: English |
| - **License**: Same as base model |
|
|
| ## Usage |
|
|
| ```python |
| from transformers import AutoTokenizer, AutoModelForCausalLM |
| |
| model = AutoModelForCausalLM.from_pretrained("YOUR_USERNAME/microsoft365_expert") |
| tokenizer = AutoTokenizer.from_pretrained("YOUR_USERNAME/microsoft365_expert") |
| |
| # Example usage |
| question = "What is data governance in Microsoft 365?" |
| inputs = tokenizer(question, return_tensors="pt") |
| outputs = model.generate(**inputs, max_new_tokens=2048) |
| response = tokenizer.decode(outputs[0], skip_special_tokens=True) |
| print(response) |
| ``` |
|
|
| ## Limitations |
|
|
| - Responses are based on training data and may not reflect the latest Microsoft 365 updates |
| - Should be used as a reference, not as the sole source for compliance decisions |
| - May require fact-checking against official Microsoft documentation |
|
|
