利用bloomz.cpp转化模型的时候出错

[dihin11]

OSError: Unable to load weights from pytorch checkpoint file for './bigscience/bloomz-7b1/pytorch_model.bin' at './bigscience/bloomz-7b1/pytorch_model.bin'. If you tried to load a PyTorch model from a TF 2.0 checkpoint, please set from_tf=True.

如果将from_tf设置为true的话，又会收到以下错误：
Loading model: ./bigscience/bloomz-7b1
Traceback (most recent call last):
File "/home/ubuntu/bloomz.cpp/convert-hf-to-ggml.py", line 84, in
model = AutoModelForCausalLM.from_pretrained(model_name, config=config, torch_dtype=torch.float16 if ftype == 1 else torch.float32, low_cpu_mem_usage=True, from_tf=True)
File "/usr/local/lib/python3.10/dist-packages/transformers/models/auto/auto_factory.py", line 471, in from_pretrained
return model_class.from_pretrained(
File "/usr/local/lib/python3.10/dist-packages/transformers/modeling_utils.py", line 2613, in from_pretrained
model, loading_info = load_tf2_checkpoint_in_pytorch_model(
File "/usr/local/lib/python3.10/dist-packages/transformers/modeling_tf_pytorch_utils.py", line 407, in load_tf2_checkpoint_in_pytorch_model
tf_model_class = getattr(transformers, tf_model_class_name)
File "/usr/local/lib/python3.10/dist-packages/transformers/utils/import_utils.py", line 1119, in getattr
raise AttributeError(f"module {self.name} has no attribute {name}")
AttributeError: module transformers has no attribute TFBloomForCausalLM

[bestpredicts]

bloomz.cpp目前看上去官方实现上面可能存在问题，我们预计本周会发布一个8bit量化的版本和提供对应的推理代码.

[Yif1999]

bloomz.cpp目前看上去官方实现上面可能存在问题，我们预计本周会发布一个8bit量化的版本和提供对应的推理代码.

将会支持连续对话嘛

[bestpredicts]

bloomz.cpp目前看上去官方实现上面可能存在问题，我们预计本周会发布一个8bit量化的版本和提供对应的推理代码.

将会支持连续对话嘛
会的，目前的模型也可以进行多轮对话推理，只需要通过拼接上文，但是我们开源的版本暂时没有针对连续对话进行优化。后续会有针对连续对话优化的版本开源。欢迎持续关注我们项目。

[Soulscb]

请问你的问题解决了吗

[Soulscb]

我这边也遇到了相同的问题 AttributeError: module transformers has no attribute TFBloomForCausalLM