Models
eventcatalog@2.24.2
Dual-license
EventCatalog Chat is currently in beta. If you find any issues, please let us know on Discord.
EventCatalog Chat supports a wide range of large language models, including DeepSeek, Llama, Gemma and more.
Through testing we found these two models work well (small, fast and give good results):
But feel free to experiment with other models and parameters to find the best model for your catalog.
Configuring your model
To configure your model, you need to update the eventcatalog.config.js
file.
// rest of the config...
chat: {
enabled: true,
// model value, default is Hermes-3-Llama-3.2-3B-q4f16_1-MLC
model: 'Hermes-3-Llama-3.2-3B-q4f16_1-MLC',
// max tokens for your model (default 4096)
max_tokens: 4096,
// number of results to match in the vector search (50 by default)
similarityResults: 50
}
Some models are larger than others and may take longer to load, smaller models may be less accurate, but you have the freedom to experiment with the best model for your catalog.
List of models for EventCatalog
Models vary in size and performance, we recommend you to experiment with the best model for your catalog.
Smaller models are faster but may be less accurate, but larger models are more accurate but may be slower to download and load.
DeepSeek
- DeepSeek R1 Distill Qwen 7B (q4f16)
- model value:
DeepSeek-R1-Distill-Qwen-7B-q4f16_1-MLC
- model value:
- DeepSeek R1 Distill Qwen 7B (q4f32)
- model value:
DeepSeek-R1-Distill-Qwen-7B-q4f32_1-MLC
- model value:
- DeepSeek R1 Distill Llama 8B (q4f16)
- model value:
DeepSeek-R1-Distill-Llama-8B-q4f16_1-MLC
- model value:
- DeepSeek R1 Distill Llama 8B (q4f32)
- model value:
DeepSeek-R1-Distill-Llama-8B-q4f32_1-MLC
- model value:
Llama (Meta)
- Tiny Llama 1.1B - (1k)
- model value:
TinyLlama-1.1B-Chat-v0.4-q4f32_1-MLC-1k
- model value:
- Llama-2-7b-chat-hf-q4f16_1-MLC
- model value:
Llama-2-7b-chat-hf-q4f16_1-MLC
- model value:
- Llama-2-7b-chat-hf-q4f32_1-MLC-1k
- model value:
Llama-2-7b-chat-hf-q4f32_1-MLC-1k
- model value:
- Llama-2-13b-chat-hf-q4f16_1-MLC
- model value:
Llama-2-13b-chat-hf-q4f16_1-MLC
- model value:
- Llama-3-8B-Instruct-q4f16_1-MLC
- model value:
Llama-3-8B-Instruct-q4f16_1-MLC
- model value:
- Llama-3-8B-Instruct-q4f32_1-MLC-1k
- model value:
Llama-3-8B-Instruct-q4f32_1-MLC-1k
- model value:
- Llama-3-70B-Instruct-q3f16_1-MLC
- model value:
Llama-3-70B-Instruct-q3f16_1-MLC
- model value:
Gemma (Google)
- Gemma 2B
- model value:
gemma-2b-it-q4f32_1-MLC
- model value:
- Gemma2 2B
- model value:
gemma-2-2b-it-q4f32_1-MLC
- model value:
- Gemma2 2B - (1k)
- model value:
gemma-2-2b-it-q4f32_1-MLC-1k
- model value:
- Gemma2 9B
- model value:
gemma-2-9b-it-q4f32_1-MLC
- model value:
- Gemma2 9B - (1k)
- model value:
gemma-2-9b-it-q4f32_1-MLC-1k
- model value:
Other models
EventCatalog uses WebLLM to load models into your browser. Any model that is supported by WebLLM is supported by EventCatalog. You can find a list of models supported by WebLLM here.
Got a question? Or want to contribute?
Found a good model for your catalog? Please let us know on Discord. Or if you need help configuring your model, please join us on Discord.