Model allows users to generate custom behavior analysis code following DeepLabCut pose-estimations.

ollama run FarhanAugustine/gemma2:27b_DLC_q4_0_

curl http://localhost:11434/api/chat \
  -d '{
    "model": "FarhanAugustine/gemma2:27b_DLC_q4_0_",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

from ollama import chat

response = chat(
    model='FarhanAugustine/gemma2:27b_DLC_q4_0_',
    messages=[{'role': 'user', 'content': 'Hello!'}],
)
print(response.message.content)

import ollama from 'ollama'

const response = await ollama.chat({
  model: 'FarhanAugustine/gemma2:27b_DLC_q4_0_',
  messages: [{role: 'user', content: 'Hello!'}],
})
console.log(response.message.content)

Models

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Name

1 model

Size

Context

Input

gemma2:27b_DLC_q4_0_

5.4GB · 8K context window · Text · 1 year ago

gemma2:27b_DLC_q4_0_

5.4GB

Text

Readme

Dynamic Animal Behavior Analysis

Associated GitHub Repo and Project Files: https://github.com/farhanaugustine/DABA-Dynamic_Animal_Behavior_Analysis