Supported Models and Hardware
Text Generation Inference enables serving optimized models on specific hardware for the highest performance. The following sections list which models are hardware are supported.
Supported Models
The following models are optimized and can be served with TGI, which uses custom CUDA kernels for better inference. You can add the flag --disable-custom-kernels at the end of the docker run command if you wish to disable them.
- BLOOM
- FLAN-T5
- Galactica
- GPT-2
- GPT-Neox
- Llama
- OPT
- SantaCoder
- Starcoder
- Falcon 7B
- Falcon 40B
- MPT
- Llama V2
- Code Llama
- Mistral
- Mixtral
- Phi
- Idefics (Multimodal)
- Llava-next (Multimodal)
If the above list lacks the model you would like to serve, depending on the model’s pipeline type, you can try to initialize and serve the model anyways to see how well it performs, but performance isn’t guaranteed for non-optimized models:
# for causal LMs/text-generation models
AutoModelForCausalLM.from_pretrained(<model>, device_map="auto")`
# or, for text-to-text generation models
AutoModelForSeq2SeqLM.from_pretrained(<model>, device_map="auto")If you wish to serve a supported model that already exists on a local folder, just point to the local folder.
text-generation-launcher --model-id <PATH-TO-LOCAL-BLOOM>