Comments (1)
我看了一下, 似乎新版的 transformer 可以直接进行量化后使用, 不需要 额外的量化过程?
model_id = "meta-llama/Llama-2-13b-chat-hf"
nf4_config = BitsAndBytesConfig(load_in_4bit=True,
bnb_4bit_quant_type="nf4",
bnb_4bit_use_double_quant=True,
bnb_4bit_compute_dtype=torch.bfloat16)
model_nf4 = AutoModelForCausalLM.from_pretrained(model_id,
quantization_config=nf4_config)
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Related Issues (20)
- 请问要怎么改docker 网站分享的port 从7860换成其他port HOT 1
- 可以支持多GPU吗
- 执行bash make-7b-cn.sh时报错 HOT 2
- 执行bash scripts/make-7b-cn.sh,最终报错ERROR: failed to solve: soulteary/llama2:base: docker.io/soulteary/llama2:base: not found HOT 2
- 【提醒】如果你没有找到 llama2:base 容器镜像
- 希望取得联系
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- ValueError HOT 4
- 接下来一些计划折腾的事(可以评论提你的想法) HOT 5
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- soulteary/llama2:base not found HOT 4
- 有支持70b的计划么,想要体验下。
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