transformers endpoints_compatible region:us
# Hydra Decoder ([Codebase](https://github.com/TCtower/Hydra))

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We currently support inference in the single GPU and batch size 1 setting, which is consistent with Medusa and is also the most common setup for local model hosting. 

**Model Weights.** We uploaded three model weights for users to try. 

| Base Model | Description | Hugging Face Repo |
| --- | ----------- | --- |
| Vicuna-7b | Medusa Model (Original) | [FasterDecoding/medusa-vicuna-7b-v1.3](https://huggingface.co/FasterDecoding/medusa-vicuna-7b-v1.3) |
| Vicuna-7b | Medusa Model - 3 Head (Ours) | [Rango2000/medusa-3h-vicuna-7b-v1.3](https://huggingface.co/Rango2000/medusa-3h-vicuna-7b-v1.3) |
| Vicuna-7b | Hydra Model - 3 Head - 1 Decoding Layer (Ours) | [shiqihe/hydra-decoder-1l-vicuna-7b-v1.3](https://huggingface.co/shiqihe/hydra-decoder-1l-vicuna-7b-v1.3) |
| Vicuna-7b | Hydra Model - 3 Head - 2 Decoding Layer (Ours) | [shiqihe/hydra-decoder-2l-vicuna-7b-v1.3](https://huggingface.co/shiqihe/hydra-decoder-2l-vicuna-7b-v1.3) |

**Inference.** You can use the following command to launch a CLI interface:

```bash
# optional
CUDA_VISIBLE_DEVICES=0
# run cli
python -m medusa.inference.cli --model [path/repo of hydra decoder]
````

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license: mit
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