Update README: change base model to Llama-3.1-70B and improve formatting

README.md

@@ -1,6 +1,6 @@
 ---
 license: llama2
-base_model: meta-llama/Llama-3.1-70B-Instruct
+base_model: meta-llama/Llama-3.1-70B
 tags:
 - maritime
 - navigation
@@ -17,11 +17,11 @@ library_name: transformers
 
 # 🌊 Llamarine - Maritime Navigation Model
 
-Llamarine is a specialized large language model fine-tuned for maritime navigation and seamanship. This is a merged version combining the base Llama-3.1-70B-Instruct model with maritime-specific LoRA adapters.
+Llamarine is a specialized large language model fine-tuned for maritime navigation and seamanship. This is a merged version combining the base Llama-3.1-70B model with maritime-specific LoRA adapters.
 
 ## 🚢 Model Details
 
-- **Base Model**: meta-llama/Llama-3.1-70B-Instruct
+- **Base Model**: meta-llama/Llama-3.1-70B
 - **Specialization**: Maritime navigation, seamanship, and nautical operations
 - **Model Type**: Merged (base + LoRA adapters)
 - **Model Size**: ~70.6B parameters
@@ -33,6 +33,7 @@ Llamarine is a specialized large language model fine-tuned for maritime navigati
 This model excels in:
 
 ### 🧭 Navigation & Piloting
+
 - Celestial navigation principles
 - GPS and electronic navigation
 - Dead reckoning and position fixing
@@ -41,6 +42,7 @@ This model excels in:
 - Tide and current calculations
 
 ### 🛥️ Ship Operations
+
 - Anchoring procedures and techniques
 - Docking and undocking maneuvers  
 - Ship handling in various conditions
@@ -48,18 +50,21 @@ This model excels in:
 - Emergency procedures
 
 ### 📡 Maritime Communications
+
 - Radio protocols and procedures
 - Distress and safety communications
 - Port communications
 - International signal codes
 
 ### ⚖️ Maritime Law & Regulations
+
 - International collision regulations (COLREGS)
 - Maritime traffic separation schemes
 - Port state control requirements
 - International maritime conventions
 
 ### 🌊 Weather & Oceanography
+
 - Weather routing and planning
 - Ocean currents and their effects
 - Storm avoidance techniques
@@ -68,6 +73,7 @@ This model excels in:
 ## 🚀 Usage
 
 ### Using Transformers
+
 ```python
 from transformers import AutoTokenizer, AutoModelForCausalLM
 import torch
@@ -95,6 +101,7 @@ print(response)
 ```
 
 ### Using vLLM (Recommended for Production)
+
 ```python
 from vllm import LLM, SamplingParams
 
@@ -132,6 +139,7 @@ print(outputs[0].outputs[0].text)
 ## 💡 Example Prompts
 
 ### Navigation Questions
+
 ```
 "What is celestial navigation?"
 "How do you plot a course using GPS?"
@@ -140,6 +148,7 @@ print(outputs[0].outputs[0].text)
 ```
 
 ### Ship Operations
+
 ```
 "What are the steps for anchoring in emergency conditions?"
 "How do you perform a man overboard maneuver?"
@@ -148,6 +157,7 @@ print(outputs[0].outputs[0].text)
 ```
 
 ### Safety & Regulations
+
 ```
 "What are the COLREGS rules for overtaking?"
 "How do you signal distress at sea?"
@@ -166,11 +176,13 @@ print(outputs[0].outputs[0].text)
 ## 🔧 Hardware Requirements
 
 ### Minimum Requirements
+
 - **RAM**: 80GB+ system RAM
 - **VRAM**: 80GB+ GPU memory (A100 recommended)
 - **Storage**: 200GB+ available space
 
 ### Recommended Setup
+
 - **GPUs**: 2x NVIDIA A100 (80GB each)
 - **RAM**: 128GB+ system RAM
 - **Storage**: NVMe SSD for optimal loading speed
@@ -178,6 +190,7 @@ print(outputs[0].outputs[0].text)
 ## 📚 Training Data
 
 This model was fine-tuned on maritime navigation data including:
+
 - Navigation textbooks and manuals
 - Maritime regulations and procedures
 - Ship handling guides
@@ -192,6 +205,6 @@ This model is part of the Llamarine project aimed at advancing AI assistance in
 
 This model inherits the Llama 2 license from the base model. Please review the license terms before commercial use.
 
-## 🌊 Fair Winds and Following Seas!
+## 🌊 Fair Winds and Following Seas
 
 *"The sea, once it casts its spell, holds one in its net of wonder forever."* - Jacques Cousteau