Create README.md

README.md

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+---
+base_model:
+- mistralai/Mistral-7B-Instruct-v0.2
+pipeline_tag: question-answering
+---
+#Introduction
+# SRED Analysis Model
+
+This model is fine-tuned for analyzing SRED (Scientific Research and Experimental Development) content, specifically for Box 242 analysis.
+
+## Usage
+
+Example input format:
+```json
+{
+  "inputs": {
+    "messages": [
+      {
+        "role": "system",
+        "content": "You are an expert SRED technical writer analyzing Box 242 content."
+      },
+      {
+        "role": "user",
+        "content": "Analyze the following technological uncertainties..."
+      }
+    ]
+  },
+  "parameters": {
+    "temperature": 0.7,
+    "max_length": 1000
+  }
+}
+
+#Getting Started
+##Activate Virtual Environment
+python3 -m venv .venv
+source .venv/bin/activate
+pip install --upgrade pip
+
+# Ensure virtual environment is activated for pip install upgrade, otherwise there may be conflicts with your global environment
+
+#For M2 Silicon Apple Chip
+##install in this exact order:
+pip3 install --pre torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/nightly/cpu
+pip install transformers==4.34.0
+pip install datasets==2.14.0
+pip install accelerate==0.24.0
+pip install bitsandbytes==0.41.1
+pip install wandb==0.15.12
+pip install sentencepiece==0.1.99
+
+##Finally install:
+pip install peft==0.4.0
+
+#For non-MX chips
+##install in this order:
+pip install transformers
+pip install datasets
+pip install accelerate
+pip install bitsandbytes
+pip install peft
+pip install wandb
+pip install torch
+pip install sentencepiece
+
+#For all users
+pip install scipy
+pip install easygui
+pip install numpy==1.24.3
+pip install python-dotenv
+
+#Training setup
+To create and upload required files to Hugging Face, run: python setup_files.py
+To test your setup: run python test_setup.py
+You will need to connect to WandB via WanB CLI
+Update the .env file with your Hugging Face token, Hugging Face model name, and WandB token
+The file should automatically push to Hugging Face
+
+#Pushing just the model (no training)
+If you need to just push the model, you can use: python push_model.py