Adding `safetensors` variant of this model
This is an automated PR created with https://huggingface.co./spaces/safetensors/convert
This new file is equivalent to pytorch_model.bin but safe in the sense that
no arbitrary code can be put into it.
These files also happen to load much faster than their pytorch counterpart:
https://colab.research.google.com/github/huggingface/notebooks/blob/main/safetensors_doc/en/speed.ipynb
The widgets on your model page will run using this model even if this is not merged
making sure the file actually works.
If you find any issues: please report here: https://huggingface.co./spaces/safetensors/convert/discussions
Feel free to ignore this PR.
Kind of scary to see this as being automated.
no way to trust that these new files are not manipulated.
Also, no reason to put duplicate content in a source repo.
hi @Suparious ! this is from the official bot. You can run the conversion script yourself and check that the output is identical.
Note that safetensors files are inherently safer than .bin
Of course it's up to you, feel free to not merge if you prefer!
| no way to trust that these new files are not manipulated.
You can easily load both to check for consistency:
from huggingface_hub import hf_hub_download
import torch
from safetensors.torch import load_file
for i in range(1, 3):
pt_filename = f"pytorch_model-0000{i}-of-00002.bin"
sf_filename = f"model-0000{i}-of-00002.safetensors"
pt_filename = hf_hub_download("cognitivecomputations/dolphin-2.1-mistral-7b", filename=pt_filename)
sf_filename = hf_hub_download("cognitivecomputations/dolphin-2.1-mistral-7b", filename=sf_filename, revision="refs/pr/21")
original = torch.load(pt_filename)
new = load_file(sf_filename)
for k, v in original.items():
torch.testing.assert_close(v, new[k])
print(f"{k} is OK")
| no reason to put duplicate content in a source repo.
I'm not sure you understand the seriousness of what pickle files enable an attacker to do on your machine.
And what an attacker could do if he got hold of anyone with write credentials in your company by modifying those weight files to everyone that is using your models.
This is not a necessary vector, it's as simple to moving to safetensors, really. (Plus the speed benefits).
Internally at HF, we're mostly banning the presence of pickle files in any production system just to give you an idea.
from huggingface_hub import hf_hub_download
import torch
from safetensors.torch import load_file
for i in range(1, 3):
pt_filename = f"pytorch_model-0000{i}-of-00002.bin"
sf_filename = f"model-0000{i}-of-00002.safetensors"
pt_filename = hf_hub_download("cognitivecomputations/dolphin-2.1-mistral-7b", filename=pt_filename)
sf_filename = hf_hub_download("cognitivecomputations/dolphin-2.1-mistral-7b", filename=sf_filename, revision="refs/pr/21")
original = torch.load(pt_filename)
new = load_file(sf_filename)
for k, v in original.items():
torch.testing.assert_close(v, new[k])
print(f"{k} is OK")
Thank-you for this example.
| no reason to put duplicate content in a source repo.
I'm not sure you understand the seriousness of what pickle files enable an attacker to do on your machine.
Yes, this was 100% accurate. Thank-you for your patience and understanding.
Internally at HF, we're mostly banning the presence of pickle files in any production system just to give you an idea.
We appreciate your detailed explanation with thoughtful reasoning. We will have to bring this up internally.
@ehartford - This safetensor file appears to match the pickle version. I'll leave it to you, if you want to merge.