| Availability |
Odoo Online
Odoo.sh
On Premise
|
| Odoo Apps Dependencies |
Discuss (mail)
|
| Community Apps Dependencies | Show |
| Lines of code | 1669 |
| Technical Name |
llm_training |
| License | LGPL-3 |
| Website | https://github.com/apexive/odoo-llm |
| Versions | 16.0 18.0 |
| Availability |
Odoo Online
Odoo.sh
On Premise
|
| Odoo Apps Dependencies |
Discuss (mail)
|
| Community Apps Dependencies | Show |
| Lines of code | 1669 |
| Technical Name |
llm_training |
| License | LGPL-3 |
| Website | https://github.com/apexive/odoo-llm |
| Versions | 16.0 18.0 |
LLM Training
Fine-tune LLM models with your own data
Key Features
Multi-Provider Support
Fine-tune models across different LLM providers from a single interface
Dataset Management
Create, validate and manage training datasets for optimal fine-tuning
Job Monitoring
Track training progress and metrics in real-time
Provider Integration
Seamless integration with leading LLM providers:
OpenAI
Fine-tune GPT models with your proprietary data
Standardized Interface
Consistent API for all providers with provider-specific optimizations
Extensible Architecture
Easily add support for additional LLM providers
User Interface
Access and manage training jobs through a simple, intuitive interface:
- Access Training Jobs: Navigate to LLM > Training > Jobs to view and manage all training jobs
- View Datasets: Access LLM > Training > Datasets to manage training data
- Monitor Status: Track job progress through the status bar and detailed metrics
- View Results: Access training results and metrics in the Results tab
Training Workflow
Create and manage training jobs with a streamlined workflow:
- Create Job: Click "Create" button to add a new training job
- Configure Job: Select provider, base model, and datasets
- Set Parameters: Configure hyperparameters for optimal training
- Submit Job: Click "Submit" to start the training process
- Monitor Progress: Track job status and metrics in real-time
Training Process
Data Preparation
Datasets are validated, formatted, and prepared for training
Model Fine-tuning
Base models are fine-tuned with your data using provider-specific methods
Result Integration
Fine-tuned models are automatically added to your available models
For more information, visit our GitHub repository
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