- Updated the Modelfile path in `pull-deepseek-model.sh` to use an absolute path for model files.
- Simplified the model loading process by removing unnecessary directory changes and directly referencing the mounted Modelfile.
- Added a new Jupyter notebook `ollama.ipynb` that demonstrates the usage of the Ollama API with a sample query and error handling for unsupported tools.
- Created README.md for Ollama Docker setup with instructions for running and using models.
- Added docker-compose.yml for Ollama service configuration.
- Introduced scripts for model setup, including pulling models from Hugging Face and loading them into Ollama.
- Implemented AI launcher script to choose between Ollama and LlamaCPP backends.
- Added GPU support scripts for LlamaCPP with detailed logging and error handling.
- Included simple model pull script for easier model management.
- Established a structured approach for model management and integration with Ollama API.
This script allows users to easily enable or disable NVIDIA persistence mode and adjust the performance state of the GPU. It includes options to set the clock speeds and reload the NVIDIA Unified Memory kernel module. Usage instructions are provided for clarity.
- Introduced a new Jupyter notebook `unsloth_nb.ipynb` for utilizing the Unsloth library.
- Implemented code to load and patch FastLanguageModel and FastQwen2Model for improved training speed.
- Configured models to support 4-bit quantization for reduced memory usage.
- Included detailed logging for model loading and system specifications.
- Implemented AirTemperature component to display average temperature and readings by station.
- Created FourDayOutlook component for displaying a four-day weather outlook.
- Added MapComponents for handling map invalidation and centering.
- Developed TwoHourForecast component to show forecasts for the next two hours with area selection.
- Built WeatherMap component to visualize temperature and wind data on a map.
- Introduced WeatherStatistics component to summarize weather conditions across areas.
- Created WindDirection component to calculate and display average wind direction.
- Added utility function to get weather icons based on forecast descriptions.
- Updated type definitions in `types.gen.ts` to use consistent formatting and remove unnecessary line breaks.
- Renamed types for better readability, such as changing `BodyLoginLoginAccessToken` to `Body_login_login_access_token`.
- Consolidated similar types and ensured all properties are consistently formatted.
- Added new types for item and user operations to enhance API interaction.
- Improved documentation comments for query parameters in weather-related data types.
- Introduced new types for air temperature, wind direction, lightning, and WBGT data.
- Updated existing types for user and item management.
- Created a new client configuration file to initialize the API client with default options.
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