OpenThinker-abliterated
Collection
1 item • Updated
How to use huihui-ai/OpenThinker-7B-abliterated with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-generation", model="huihui-ai/OpenThinker-7B-abliterated")
messages = [
{"role": "user", "content": "Who are you?"},
]
pipe(messages) # Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("huihui-ai/OpenThinker-7B-abliterated")
model = AutoModelForCausalLM.from_pretrained("huihui-ai/OpenThinker-7B-abliterated")
messages = [
{"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
messages,
add_generation_prompt=True,
tokenize=True,
return_dict=True,
return_tensors="pt",
).to(model.device)
outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))How to use huihui-ai/OpenThinker-7B-abliterated with vLLM:
# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "huihui-ai/OpenThinker-7B-abliterated"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
-H "Content-Type: application/json" \
--data '{
"model": "huihui-ai/OpenThinker-7B-abliterated",
"messages": [
{
"role": "user",
"content": "What is the capital of France?"
}
]
}'docker model run hf.co/huihui-ai/OpenThinker-7B-abliterated
How to use huihui-ai/OpenThinker-7B-abliterated with SGLang:
# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
--model-path "huihui-ai/OpenThinker-7B-abliterated" \
--host 0.0.0.0 \
--port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
-H "Content-Type: application/json" \
--data '{
"model": "huihui-ai/OpenThinker-7B-abliterated",
"messages": [
{
"role": "user",
"content": "What is the capital of France?"
}
]
}'docker run --gpus all \
--shm-size 32g \
-p 30000:30000 \
-v ~/.cache/huggingface:/root/.cache/huggingface \
--env "HF_TOKEN=<secret>" \
--ipc=host \
lmsysorg/sglang:latest \
python3 -m sglang.launch_server \
--model-path "huihui-ai/OpenThinker-7B-abliterated" \
--host 0.0.0.0 \
--port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
-H "Content-Type: application/json" \
--data '{
"model": "huihui-ai/OpenThinker-7B-abliterated",
"messages": [
{
"role": "user",
"content": "What is the capital of France?"
}
]
}'How to use huihui-ai/OpenThinker-7B-abliterated with Docker Model Runner:
docker model run hf.co/huihui-ai/OpenThinker-7B-abliterated
This is an uncensored version of open-thoughts/OpenThinker-7B created with abliteration (see remove-refusals-with-transformers to know more about it).
This is a crude, proof-of-concept implementation to remove refusals from an LLM model without using TransformerLens.
You can use huihui_ai/openthinker-abliterated directly
ollama run huihui_ai/openthinker-abliterated
bc1qqnkhuchxw0zqjh2ku3lu4hq45hc6gy84uk70ge
Base model
Qwen/Qwen2.5-7B