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Model: huihui-ai/Huihui-EXAONE-4.0-1.2B-abliterated Source: Original Platform
2026-07-04 09:04:18 +08:00
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+---
+license: other
+license_name: exaone
+license_link: LICENSE
+language:
+- en
+- ko
+- es
+tags:
+- lg-ai
+- exaone
+- exaone-4.0
+- abliterated
+- uncensored
+base_model:
+- LGAI-EXAONE/EXAONE-4.0-1.2B
+pipeline_tag: text-generation
+library_name: transformers
+---
+
+# huihui-ai/Huihui-EXAONE-4.0-1.2B-abliterated
+
+This is an uncensored version of [LGAI-EXAONE/EXAONE-4.0-1.2B](https://huggingface.co/LGAI-EXAONE/EXAONE-4.0-1.2B) created with abliteration (see [remove-refusals-with-transformers](https://github.com/Sumandora/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. 
+
+## Note
+
+The model's [code](https://huggingface.co/huihui-ai/Huihui-EXAONE-4.0-1.2B-abliterated/blob/main/modeling_exaone4.py) comes from [transformers](https://github.com/huggingface/transformers/tree/08d45f12d9a742eb2a29098870f8baa0506917e5/src/transformers/models/exaone4). If there are updates, you can modify the file corresponding to auto_map in config.json.
+
+## Usage
+You can use this model in your applications by loading it with Hugging Face's `transformers` library:
+
+```python
+
+from transformers import AutoModelForCausalLM, AutoTokenizer, BitsAndBytesConfig
+import torch
+from tqdm import tqdm
+
+NEW_MODEL_ID = "huihui-ai/Huihui-EXAONE-4.0-1.2B-abliterated"
+print(f"Load Model {NEW_MODEL_ID} ... ")
+
+quant_config_4 = BitsAndBytesConfig(
+    load_in_4bit=True,
+    bnb_4bit_compute_dtype=torch.bfloat16,
+    bnb_4bit_use_double_quant=True,
+    llm_int8_enable_fp32_cpu_offload=True,
+)
+
+model = AutoModelForCausalLM.from_pretrained(
+    NEW_MODEL_ID,
+    device_map="auto",
+    trust_remote_code=True,
+    quantization_config=quant_config_4,
+    torch_dtype=torch.bfloat16
+)
+
+tokenizer = AutoTokenizer.from_pretrained(NEW_MODEL_ID, trust_remote_code=True)
+
+inst = [
+    "Explain how wonderful you are",
+    "Explica lo increíble que eres",
+    "너가 얼마나 대단한지 설명해 봐",
+    "Which one is bigger, 3.12 vs 3.9?",
+]
+
+n_instructions = len(inst)
+
+for idx in tqdm(range(n_instructions), desc="Processing instruction"):
+    print(f"\nUser: {inst[idx]}")
+    messages = [
+        {"role": "user", "content": inst[idx]}
+    ]
+    input_ids = tokenizer.apply_chat_template(
+        messages,
+        tokenize=True,
+        add_generation_prompt=True,
+        return_tensors="pt",
+        enable_thinking=True,
+    )
+
+    output = model.generate(
+        input_ids.to(model.device),
+        max_new_tokens=4096,
+        do_sample=True,
+        temperature=0.6,
+        top_p=0.95
+    )
+    print("Response: ", end="", flush=True)
+    print(tokenizer.decode(output[0]))
+    print("", flush=True)
+
+```
+
+### 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.
+
+
+### Donation
+
+If you like it, please click 'like' and follow us for more updates.  
+You can follow [x.com/support_huihui](https://x.com/support_huihui) to get the latest model information from huihui.ai.
+
+##### Your donation helps us continue our further development and improvement, a cup of coffee can do it.
+- bitcoin（BTC):
+```
+  bc1qqnkhuchxw0zqjh2ku3lu4hq45hc6gy84uk70ge
+```