SDSC/open-pulse-hackathon-data-analysis huggingface dataset:
Repository: sdsc-ordes/saving-willy
Description: Research Data Infrastructure for cetacean identification
Primary language: Python

---
title: Saving Willy
emoji: 🐋
colorFrom: indigo
colorTo: blue
sdk: streamlit
sdk_version: 1.39.0
python_version: "3.10"
app_file: src/main.py
pinned: false
license: apache-2.0
short_description: 'SDSC Hackathon - Project 10. '
---



Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py is the one and only app


## Install

```
git clone git@hf.co:spaces/Saving-Willy/saving-willy-space

pip install -r requirements.txt 
```

```
streamlit run app.py 
```


## Test data

https://www.kaggle.com/competitions/happy-whale-and-dolphin/data




Have a lot of fun!
Repository: sdsc-ordes/sdschat
Primary language: Shell
Topics: ai, containers

# sdschat

Fastchat implementation for SDSC. 

## How to run this app in SDSC

```
runai submit sdschat-$USER -i caviri/sdschat:latest --service-type=portforward --port 8000:8000 --port 7860:7860 --attach --interactive --node-type "A100" -g 0.5
```

## How to build this image?

```
docker build -t caviri/sdschat:latest . 
```

```
docker push caviri/sdschat:latest
```

```
docker run -it --rm -p 7860:7860 -p 8000:8000 --gpus all caviri/sdschat:latest 
```

Add as many huggingface models as you want to use in `MODELS`. Separate each model by a comma. 

```
docker run -it --rm -p 7860:7860 -p 8000:8000 -e MODELS="lmsys/fastchat-t5-3b-v1.0,lmsys/vicuna-7b-v1.3" --gpus all caviri/sdschat:root 
```

If you want to use the OPENAI API. Use the variable: `-e OPENAIMODEL="nomic-ai/gpt4all-13b-snoozy"`