403 Client Error: Forbidden for url:
hi guys, I have this problem using paraphrase-distilroberta-base-v2 model.once I call the model through in my python code:model = SentenceTransformer(‘sentence-transformers/paraphrase-distilroberta-base-v2’)this error appear:403 Client Error: Forbidden for url:https://huggingface.co/sentence-transformers/distiluse-base-multilingual-cased-v2/resolve/486c69f0e5395a86ef58883e1c18e475cc7b8aba/.gitattributessame thing if I use  Hosted inference API in model main page.Some advise about this problem?
2021-12-06T12:50:42Z
Hi@giovanni94s,I guess there is today a problem in the Hugging Face hub as I even can not edit a model or a datasets card in my profile.@julien-ccan you help us? Thank you.
2021-12-06T14:26:53Z
I’m also facing the issue for a different model, both in production code and as well as the hosted API.Cannot GET /sentence-transformers/multi-qa-MiniLM-L6-cos-v1/resolve/1de23253abdbc620a58070d408055cc9a8439375For now, I copied the model and loaded it from the local path. I would like to know why it errored out as well.
2021-12-06T14:28:09Z
@sasikirancan you show me how to copy the model and load it locally?
2021-12-06T14:28:50Z
Having the same issue with ‘sentence-transformers/all-mpnet-base-v2’. I saw there was an earlier thread on this tooBatch transform inference job - downloading model from the Hugging Face Hub on start upAmazon SageMakerI try to run 

However I get this error: 
requests.exceptions.HTTPError: 403 Client Error: Forbidden for url: [https://huggingface.co/api/models/cardiffnlp/twitter-roberta-base-sentiment] 
It looks like an instance created by AWS SageMaker (client) is not allowed to download the model. Something specific I need to add in the role I use with AWS Sagemaker? 
or there is an issue with a token in 
model_info = _api.model_info(repo_id=model_id, revision=revision, token=use_auth_token) 
Thanks, 
KateWeirdly, I’m only getting it when trying to run batch on sagemakerwhere I do it locally it works fine egmodel = AutoModel.from_pretrained(‘sentence-transformers/paraphrase-distilroberta-base-v2’)andmodel = AutoModel.from_pretrained(‘sentence-transformers/all-mpnet-base-v2’)Checking the cloud logThis is an experimental beta features, which allows downloading model from the Hugging Face Hub on start up. It loads the model defined in the env varHF_MODEL_IDThen immediately followed by the 403 error
2021-12-06T14:31:37Z
@giovanni94sI was able to find the cached model located at:~/.cache/torch/sentence_transformers.I then copied the model directory to./modelsand used:model = SentenceTransformer('./models/sentence-transformers_multi-qa-MiniLM-L6-cos-v1')to load it from the local path. I believe it should be possible to download the model if it isn’t available in the cache directory.
2021-12-06T14:33:44Z
Weird. For me, it failed on EC2 server. Then, I loaded the model using a local path.
2021-12-06T14:35:19Z
I think is a problem from server side. Let’s wait for an answer
2021-12-06T14:40:50Z
@sasikiran@pierreguillounow the model seems to be downloaded correctly. Confirm from your side?
2021-12-06T14:53:55Z
Yes, it’s working now on the hosted API. I believe it would work on EC2 as well but for now, I would continue loading it from local path.
2021-12-06T15:20:37Z
I can edit model and dataset card butI can not create a new one from the webinside my Hugging face perfil: I still get403 Forbidden.PS: I do it inside the HF account of a organization where I’m anadminmember.createdcard2337×1164 46.4 KBcard3915×1835 32 KB
2021-12-06T16:06:49Z
I still have same issue with sagemaker no matter what model I call it seems
2021-12-07T03:56:06Z
So you run it from SageMaker Studio and receive the error but if you start a batch job from your local environment it does work?I have the same log message but I start from the local environmentThanks,Kate
2021-12-07T08:39:17Z
Hey everyone, thanks for reporting the issue - it’s now fixed so you should be able to download the pretrained models as normal
2021-12-07T10:40:30Z
Great! It Works (I can create a card for a dataset in the HF hub). Thank you@lewtun.
2021-12-07T18:12:08Z
I’m kicking off the batch job from a sagemaker notebook instance, but the batch job runs in sagemaker. It still fails with 403. I tried it from a different aws account with the same results. More detail in this threadError 403 when downloading model for Sagemaker batch inference - #6 by philschmid
2022-03-09T02:12:37Z
i’m still getting this error any advice?