Comments (3)
github-actions
commented on September 14, 2024
This issue is stale because it has been open 30 days with no activity. Remove stale label or comment or this will be closed in 5 days.
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BananPrzydawka
commented on September 14, 2024
Why automatically reject unadressed issiues? To this day i am not able to install the safetensors package
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Narsil
commented on September 14, 2024
Because issues that do not receive attention need to be removed from visible list.
It's always easy to resurect them, comment on them, like you are doing so we know they are still valid.
You are not explaining how you are trying to install at all python-safetensors is not a package maintained here so we cannot make any changes.
The error seems to suggest there is an issue with the numpy version pre-packages in the thing your referring to.
This library does not maintain a dependency on numpy nor is linked against it.
Please report this issue to whereever the package, most likely here: https://aur.archlinux.org/packages/python-safetensors
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Related Issues (20)
- safetensors.tensorflow.save modifies its input argument HOT 1
- Error when using map_location="cuda:0" with multiple GPUs HOT 1
- ModuleNotFoundError: No module named 'torch._higher_order_ops' HOT 1
- misleading error message in `safe_open` HOT 4
- Register a MIME type for the `safetensors` format. HOT 1
- README is inaccurate HOT 3
- Unable to save llama3 since complex64 is not supported HOT 1
- How to save model checkpoint from a distributed training from multiple nodes? HOT 2
- SafetensorError is not pickleable, potentially causing hangs in multi-process environments HOT 2
- inconsistent behavior of slicing in certain model file HOT 4
- get_slice has the same speed as get_tensor HOT 1
- get_tensor returns an empty tensor on LoRa safetensors adapter saved by SFTTrainer HOT 1
- pytorch: safetensors library hardcodes using CUDA if only device index is provided HOT 3
- Wrong device when using device="cpu" with torch.device HOT 3
- Problem serializing quantized weights HOT 3
- converting weight of more than 50G‘s .bin to .safetensors failed
- Some layers are not loaded(‘encoder.embed_token.weight’ and 'shared.weight') when loading converted safetensors into transfomrers.MT5EncoderModel.
- Retrieving saved metadata HOT 3
- SafetensorError does not appear in `__init__.pyi`
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