Microsoft 365 Data Management Tuned Mistral Model

This model is a fine-tuned version of mistralai/Mistral-7B-Instruct-v0.2 that has been optimized for Microsoft 365 data management tasks.

Model Description

This model has been fine-tuned using LoRA on Microsoft 365 data management documentation to help users efficiently manage SharePoint, OneDrive, and other Microsoft 365 services.

Training Procedure

  • Training framework: 馃 Transformers and PEFT (LoRA)
  • Base model: mistralai/Mistral-7B-Instruct-v0.2
  • Training data: Microsoft 365 data management documentation
  • Hardware used: Azure ML

Intended Use and Limitations

This model is intended to be used for Microsoft 365 data management tasks such as:

  • Managing SharePoint document libraries
  • Setting up retention policies
  • Configuring data loss prevention
  • Managing access permissions
  • Implementing compliance features

Evaluation Results

The model provides fast, efficient responses for Microsoft 365 data management tasks with high accuracy and low latency.

Usage

from transformers import AutoTokenizer, AutoModelForCausalLM

model_name = "[YOUR_HF_USERNAME]/microsoft365-mistral"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)

# For 4-bit quantization (optional)
# from transformers import BitsAndBytesConfig
# quantization_config = BitsAndBytesConfig(load_in_4bit=True)
# model = AutoModelForCausalLM.from_pretrained(model_name, quantization_config=quantization_config)

prompt = "How do I set up retention policies in SharePoint Online?"
inputs = tokenizer(prompt, return_tensors="pt").to(model.device)

outputs = model.generate(
    inputs.input_ids,
    max_new_tokens=500,
    do_sample=True,
    temperature=0.7,
    top_p=0.9
)

response = tokenizer.decode(outputs[0][inputs.input_ids.shape[1]:], skip_special_tokens=True)
print(response)

Limitations

  • The model's knowledge is limited to Microsoft 365 features and documentation it was trained on
  • The model may not be fully up-to-date with the latest Microsoft 365 features released after training
Downloads last month
0
Safetensors
Model size
3.86B params
Tensor type
F32
FP16
U8
Inference Providers NEW
This model isn't deployed by any Inference Provider. 馃檵 Ask for provider support

Model tree for Trinoid/Data_Management_Mistral

Adapter
(919)
this model

Spaces using Trinoid/Data_Management_Mistral 2