library_name: transformers license: other license_name: lfm1.0 license_link: LICENSE pipeline_tag: text-generation tags:
- liquid
- lfm2.5
- edge
- uncensored
- abliterix
- safetensors
- bf16 base_model:
- LiquidAI/LFM2.5-2.6B base_model_relation: finetune
parent: LiquidAI official
model_id = "SC117/LFM2.5-2.6B-Uncensored" model = AutoModelForCausalLM.from_pretrained(model_id, dtype="bfloat16") tokenizer = AutoTokenizer.from_pretrained(model_id)
messages = [{"role": "user", "content": "What is 2+2?"}] input_ids = tokenizer.apply_chat_template( messages, add_generation_prompt=True, return_tensors="pt" )["input_ids"].to(model.device)
output = model.generate( input_ids, do_sample=True, temperature=0.1, top_k=50, repetition_penalty=1.1, max_new_tokens=512, ) print(tokenizer.decode(output[0][input_ids.shape[1]:], skip_special_tokens=True))