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我们使用single-image data来lora微调InternVL2‑40B模型。 训练时,平均每小时处理1100条数据。 但在10个data上做测试时,用model.chat 总共5个小时还没跑完,请问有什么方式可以调优? 以下是chat的代码:
generation_config = dict( num_beams=1, max_new_tokens=4096, min_new_tokens=8, do_sample=False, temperature=0.0, )
The text was updated successfully, but these errors were encountered:
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我们使用single-image data来lora微调InternVL2‑40B模型。
训练时,平均每小时处理1100条数据。
但在10个data上做测试时,用model.chat 总共5个小时还没跑完,请问有什么方式可以调优?
以下是chat的代码:
generation_config = dict(
num_beams=1,
max_new_tokens=4096,
min_new_tokens=8,
do_sample=False,
temperature=0.0,
)
The text was updated successfully, but these errors were encountered: