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

tools

ollama run FarhanAugustine/llama3.3_DLC_q3_K_S

curl http://localhost:11434/api/chat \
  -d '{
    "model": "FarhanAugustine/llama3.3_DLC_q3_K_S",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

from ollama import chat

response = chat(
    model='FarhanAugustine/llama3.3_DLC_q3_K_S',
    messages=[{'role': 'user', 'content': 'Hello!'}],
)
print(response.message.content)

import ollama from 'ollama'

const response = await ollama.chat({
  model: 'FarhanAugustine/llama3.3_DLC_q3_K_S',
  messages: [{role: 'user', content: 'Hello!'}],
})
console.log(response.message.content)