Abliteration

Overview

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Required Variables

os.environ["ABLITERATION_API_KEY"] = ""  # your Abliteration API key

Sample Usage

from litellm import completion

os.environ["ABLITERATION_API_KEY"] = ""

response = completion(
    model="abliteration/abliterated-model",
    messages=[{"role": "user", "content": "Hello from LiteLLM"}],
)

print(response)

Sample Usage - Streaming

from litellm import completion

os.environ["ABLITERATION_API_KEY"] = ""

response = completion(
    model="abliteration/abliterated-model",
    messages=[{"role": "user", "content": "Stream a short reply"}],
    stream=True,
)

for chunk in response:
    print(chunk)

Usage with LiteLLM Proxy Server

1. Add the model to your proxy config:

model_list:
  - model_name: abliteration-chat
    litellm_params:
      model: abliteration/abliterated-model
      api_key: os.environ/ABLITERATION_API_KEY

2. Start the proxy:

litellm --config /path/to/config.yaml

Direct API Usage (Bearer Token)

Use the environment variable as a Bearer token against the OpenAI-compatible endpoint: https://api.abliteration.ai/v1/chat/completions.

curl https://api.abliteration.ai/v1/chat/completions \\
  -H "Authorization: Bearer ${ABLITERATION_API_KEY}" \\
  -H "Content-Type: application/json" \\
  -d '{
    "model": "abliterated-model",
    "messages": [{"role": "user", "content": "Hello from Abliteration"}]
  }'

api_key = os.environ["ABLITERATION_API_KEY"]

response = requests.post(
    "https://api.abliteration.ai/v1/chat/completions",
    headers={
        "Authorization": f"Bearer {api_key}",
        "Content-Type": "application/json",
    },
    json={
        "model": "abliterated-model",
        "messages": [{"role": "user", "content": "Hello from Abliteration"}],
    },
    timeout=60,
)

print(response.json())