huihui-ai/Huihui-Ling-mini-2.0-abliterated

This is an uncensored version of inclusionAI/Ling-mini-2.0 created with abliteration (see remove-refusals-with-transformers to know more about it).

GGUF

ggml-org/llama.cpp and im0qianqian/llama.cpp now supports conversion to GGUF format and can be tested using llama-cli.

The GGUF file has been uploaded.

Q4_K_M may sometimes refuse to respond; it is recommended to use Q8_0 or f16 instead.

llama-cli -m huihui-ai/Huihui-Ling-mini-2.0-abliterated/GGUF/ggml-model-q8_0.gguf -n 8192

Usage

from transformers import AutoModelForCausalLM, AutoTokenizer
model_name = "huihui-ai/Huihui-Ling-mini-2.0-abliterated"
model = AutoModelForCausalLM.from_pretrained(
    model_name,
    dtype="auto",
    device_map="auto",
    trust_remote_code=True,
)
tokenizer = AutoTokenizer.from_pretrained(model_name)
prompt = "Give me a short introduction to large language models."
messages = [
    {"role": "system", "content": "You are Ling, an assistant created by inclusionAI"},
    {"role": "user", "content": prompt}
]
text = tokenizer.apply_chat_template(
    messages,
    tokenize=False,
    add_generation_prompt=True
)
model_inputs = tokenizer([text], return_tensors="pt", return_token_type_ids=False).to(model.device)
generated_ids = model.generate(
    **model_inputs,
    max_new_tokens=512
)
generated_ids = [
    output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
]
response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]

Usage Warnings

• Risk of Sensitive or Controversial Outputs: This model’s safety filtering has been significantly reduced, potentially generating sensitive, controversial, or inappropriate content. Users should exercise caution and rigorously review generated outputs.

• Not Suitable for All Audiences: Due to limited content filtering, the model’s outputs may be inappropriate for public settings, underage users, or applications requiring high security.

• Legal and Ethical Responsibilities: Users must ensure their usage complies with local laws and ethical standards. Generated content may carry legal or ethical risks, and users are solely responsible for any consequences.

• Research and Experimental Use: It is recommended to use this model for research, testing, or controlled environments, avoiding direct use in production or public-facing commercial applications.

• Monitoring and Review Recommendations: Users are strongly advised to monitor model outputs in real-time and conduct manual reviews when necessary to prevent the dissemination of inappropriate content.

• No Default Safety Guarantees: Unlike standard models, this model has not undergone rigorous safety optimization. huihui.ai bears no responsibility for any consequences arising from its use.

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