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  • Developed by: ttworld2
  • License: apache-2.0
  • Finetuned from model : llm-jp/llm-jp-3-13b

This llama model was trained 2x faster with Unsloth and Huggingface's TRL library.

瀹熻鏂规硶

浠ヤ笅銇倛銇嗐仾銉椼儹銉炽儣銉堛仹瀹熻 results = [] for dt in tqdm(datasets): input = dt["input"]

prompt = f"""### 鎸囩ず\n{input}\n### 鍥炵瓟\n"""

inputs = tokenizer([prompt], return_tensors = "pt").to(model.device)

outputs = model.generate(**inputs, max_new_tokens = 512, use_cache = True, do_sample=False, repetition_penalty=1.2) prediction = tokenizer.decode(outputs[0], skip_special_tokens=True).split('\n### 鍥炵瓟')[-1]

results.append({"task_id": dt["task_id"], "input": input, "output": prediction})

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