# How to use gated models? **URL:** **Author:** ![premissa72](https://sea2.discourse-cdn.com/hellohellohello/user_avatar/discuss.huggingface.co/premissa72/32/18109_2.png) [@premissa72](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Fu%2Fpremissa72)%5C **Post date:** [September 2, 2023, 8:16am UTC](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Ft%2Fhow-to-use-gated-models%2F53234%2F1 "2023-09-02T08:16:42Z") I am testing some language models in my research. I have a problem with gated models specifically with the meta-llama/Llama-2-7b-hf. As I can only use the environment provided by the university where I work, I use docker for this purpose. With the not gated models, I had no problems but trying the llama model I am getting an error even in the case I provide my access token. The CLI cannot be used in this case, but I have managed to log in via the notebook. What is the issue? Please help with the correct process. ```auto from huggingface_hub import login login(token = 'my token') ``` It was successfull. ```auto # Load the tokenizer tokenizer = AutoTokenizer.from_pretrained("meta-llama/Llama-2-7b-hf", token='my token') ``` It has failed even I tried use\_auth\_token=True The error message: ````auto --------------------------------------------------------------------------- HTTPError Traceback (most recent call last) File ~/.local/lib/python3.10/site-packages/huggingface_hub/utils/_errors.py:261, in hf_raise_for_status(response, endpoint_name) 260 try: --> 261 response.raise_for_status() 262 except HTTPError as e: File /opt/conda/lib/python3.10/site-packages/requests/models.py:1021, in Response.raise_for_status(self) 1020 if http_error_msg: -> 1021 raise HTTPError(http_error_msg, response=self) HTTPError: 403 Client Error: Forbidden for url: https://huggingface.co/meta-llama/Llama-2-7b-hf/resolve/main/tokenizer_config.json The above exception was the direct cause of the following exception: GatedRepoError Traceback (most recent call last) File ~/.local/lib/python3.10/site-packages/transformers/utils/hub.py:417, in cached_file(path_or_repo_id, filename, cache_dir, force_download, resume_download, proxies, use_auth_token, revision, local_files_only, subfolder, repo_type, user_agent, _raise_exceptions_for_missing_entries, _raise_exceptions_for_connection_errors, _commit_hash) 415 try: 416 # Load from URL or cache if already cached --> 417 resolved_file = hf_hub_download( 418 path_or_repo_id, 419 filename, 420 subfolder=None if len(subfolder) == 0 else subfolder, 421 repo_type=repo_type, 422 revision=revision, 423 cache_dir=cache_dir, 424 user_agent=user_agent, 425 force_download=force_download, 426 proxies=proxies, 427 resume_download=resume_download, 428 use_auth_token=use_auth_token, 429 local_files_only=local_files_only, 430 ) 432 except RepositoryNotFoundError: File ~/.local/lib/python3.10/site-packages/huggingface_hub/utils/_validators.py:118, in validate_hf_hub_args.._inner_fn(*args, **kwargs) 116 kwargs = smoothly_deprecate_use_auth_token(fn_name=fn. __name__ , has_token=has_token, kwargs=kwargs) --> 118 return fn(*args, **kwargs) File ~/.local/lib/python3.10/site-packages/huggingface_hub/file_download.py:1195, in hf_hub_download(repo_id, filename, subfolder, repo_type, revision, library_name, library_version, cache_dir, local_dir, local_dir_use_symlinks, user_agent, force_download, force_filename, proxies, etag_timeout, resume_download, token, local_files_only, legacy_cache_layout) 1194 try: -> 1195 metadata = get_hf_file_metadata( 1196 url=url, 1197 token=token, 1198 proxies=proxies, 1199 timeout=etag_timeout, 1200 ) 1201 except EntryNotFoundError as http_error: 1202 # Cache the non-existence of the file and raise File ~/.local/lib/python3.10/site-packages/huggingface_hub/utils/_validators.py:118, in validate_hf_hub_args.._inner_fn(*args, **kwargs) 116 kwargs = smoothly_deprecate_use_auth_token(fn_name=fn. __name__ , has_token=has_token, kwargs=kwargs) --> 118 return fn(*args, **kwargs) File ~/.local/lib/python3.10/site-packages/huggingface_hub/file_download.py:1541, in get_hf_file_metadata(url, token, proxies, timeout) 1532 r = _request_wrapper( 1533 method="HEAD", 1534 url=url, (...) 1539 timeout=timeout, 1540 ) -> 1541 hf_raise_for_status(r) 1543 # Return File ~/.local/lib/python3.10/site-packages/huggingface_hub/utils/_errors.py:277, in hf_raise_for_status(response, endpoint_name) 274 message = ( 275 f"{response.status_code} Client Error." + "\n\n" + f"Cannot access gated repo for url {response.url}." 276 ) --> 277 raise GatedRepoError(message, response) from e 279 elif error_code == "RepoNotFound" or response.status_code == 401: 280 # 401 is misleading as it is returned for: 281 # - private and gated repos if user is not authenticated 282 # - missing repos 283 # => for now, we process them as `RepoNotFound` anyway. 284 # See https://gist.github.com/Wauplin/46c27ad266b15998ce56a6603796f0b9 GatedRepoError: 403 Client Error. (Request ID: Root=1-64f2ec62-606f496c0d95f5a34a4a0d0f;01831139-7411-49fd-9c24-89b875b4dcf0) Cannot access gated repo for url https://huggingface.co/meta-llama/Llama-2-7b-hf/resolve/main/tokenizer_config.json. Your request to access model meta-llama/Llama-2-7b-hf is awaiting a review from the repo authors. During handling of the above exception, another exception occurred: OSError Traceback (most recent call last) Cell In[25], line 2 1 # Load the tokenizer ----> 2 tokenizer = AutoTokenizer.from_pretrained("meta-llama/Llama-2-7b-hf", token='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', use_auth_token=True) File ~/.local/lib/python3.10/site-packages/transformers/models/auto/tokenization_auto.py:652, in AutoTokenizer.from_pretrained(cls, pretrained_model_name_or_path, *inputs, **kwargs) 649 return tokenizer_class.from_pretrained(pretrained_model_name_or_path, *inputs, **kwargs) 651 # Next, let's try to use the tokenizer_config file to get the tokenizer class. --> 652 tokenizer_config = get_tokenizer_config(pretrained_model_name_or_path, **kwargs) 653 if "_commit_hash" in tokenizer_config: 654 kwargs["_commit_hash"] = tokenizer_config["_commit_hash"] File ~/.local/lib/python3.10/site-packages/transformers/models/auto/tokenization_auto.py:496, in get_tokenizer_config(pretrained_model_name_or_path, cache_dir, force_download, resume_download, proxies, use_auth_token, revision, local_files_only, subfolder, **kwargs) 434 """ 435 Loads the tokenizer configuration from a pretrained model tokenizer configuration. 436 (...) 493 tokenizer_config = get_tokenizer_config("tokenizer-test") 494 ```""" 495 commit_hash = kwargs.get("_commit_hash", None) --> 496 resolved_config_file = cached_file( 497 pretrained_model_name_or_path, 498 TOKENIZER_CONFIG_FILE, 499 cache_dir=cache_dir, 500 force_download=force_download, 501 resume_download=resume_download, 502 proxies=proxies, 503 use_auth_token=use_auth_token, 504 revision=revision, 505 local_files_only=local_files_only, 506 subfolder=subfolder, 507 _raise_exceptions_for_missing_entries=False, 508 _raise_exceptions_for_connection_errors=False, 509 _commit_hash=commit_hash, 510 ) 511 if resolved_config_file is None: 512 logger.info("Could not locate the tokenizer configuration file, will try to use the model config instead.") File ~/.local/lib/python3.10/site-packages/transformers/utils/hub.py:433, in cached_file(path_or_repo_id, filename, cache_dir, force_download, resume_download, proxies, use_auth_token, revision, local_files_only, subfolder, repo_type, user_agent, _raise_exceptions_for_missing_entries, _raise_exceptions_for_connection_errors, _commit_hash) 417 resolved_file = hf_hub_download( 418 path_or_repo_id, 419 filename, (...) 429 local_files_only=local_files_only, 430 ) 432 except RepositoryNotFoundError: --> 433 raise EnvironmentError( 434 f"{path_or_repo_id} is not a local folder and is not a valid model identifier " 435 "listed on 'https://huggingface.co/models'\nIf this is a private repository, make sure to " 436 "pass a token having permission to this repo with `use_auth_token` or log in with " 437 "`huggingface-cli login` and pass `use_auth_token=True`." 438 ) 439 except RevisionNotFoundError: 440 raise EnvironmentError( 441 f"{revision} is not a valid git identifier (branch name, tag name or commit id) that exists " 442 "for this model name. Check the model page at " 443 f"'https://huggingface.co/{path_or_repo_id}' for available revisions." 444 ) OSError: meta-llama/Llama-2-7b-hf is not a local folder and is not a valid model identifier listed on 'https://huggingface.co/models' If this is a private repository, make sure to pass a token having permission to this repo with `use_auth_token` or log in with `huggingface-cli login` and pass `use_auth_token=True`. ```` ---
**Author:** ![UserDAN](https://avatars.discourse-cdn.com/v4/letter/u/9fc29f/32.png) [@UserDAN](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Fu%2FUserDAN)%5C **Post date:** [September 10, 2023, 9:28pm UTC](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Ft%2Fhow-to-use-gated-models%2F53234%2F2 "2023-09-10T21:28:40Z")
I have the same issue ---
**Author:** ![ReatKay](https://sea2.discourse-cdn.com/hellohellohello/user_avatar/discuss.huggingface.co/reatkay/32/18831_2.png) [@ReatKay](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Fu%2FReatKay)%5C **Post date:** [September 10, 2023, 10:18pm UTC](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Ft%2Fhow-to-use-gated-models%2F53234%2F3 "2023-09-10T22:18:19Z")
> [@premissa72](#): > > ```auto > tokenizer = AutoTokenizer.from_pretrained("meta-llama/Llama-2-7b-hf", token='my token') > > ``` I had the same issues when I tried the Llama-2 model with a token passed through code. I gave up after while using cli. But what I see from your error: \*\* > “Your request to access model meta-llama/Llama-2-7b-hf is awaiting a review from the repo authors.” \*\* I have an assumption. I suspect some auth response caching issues or - less likely - some extreme response caching expiration time values. As you said you could login via notebook (and access the repo, I assume?), the caching seems to be client based. While I had issues with token auth too, now it works for with token (tried from secondary environment). ---
**Author:** ![UserDAN](https://avatars.discourse-cdn.com/v4/letter/u/9fc29f/32.png) [@UserDAN](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Fu%2FUserDAN)%5C **Post date:** [September 11, 2023, 7:17am UTC](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Ft%2Fhow-to-use-gated-models%2F53234%2F4 "2023-09-11T07:17:55Z")
when can I get the approval from hugging face it has been two days ![Screenshot 2023-09-11 at 10.15.48 AM](https://us1.discourse-cdn.com/hellohellohello/original/3X/a/e/ae329387de3dc1a68104219b44dd59043263266d.png) if anyone know to can I contact them please reply to me ---
**Author:** ![ReatKay](https://sea2.discourse-cdn.com/hellohellohello/user_avatar/discuss.huggingface.co/reatkay/32/18831_2.png) [@ReatKay](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Fu%2FReatKay)%5C **Post date:** [September 11, 2023, 10:37am UTC](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Ft%2Fhow-to-use-gated-models%2F53234%2F5 "2023-09-11T10:37:22Z")
The approval does not come from hugging face, it will come from the repo owner, in this case meta. I assume during weekends their repo owner doesnt work 😉 ---
**Author:** ![UserDAN](https://avatars.discourse-cdn.com/v4/letter/u/9fc29f/32.png) [@UserDAN](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Fu%2FUserDAN)%5C **Post date:** [September 11, 2023, 12:29pm UTC](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Ft%2Fhow-to-use-gated-models%2F53234%2F6 "2023-09-11T12:29:46Z")
thank you for the replay is there any way to contact them?? ---
**Author:** ![ReatKay](https://sea2.discourse-cdn.com/hellohellohello/user_avatar/discuss.huggingface.co/reatkay/32/18831_2.png) [@ReatKay](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Fu%2FReatKay)%5C **Post date:** [September 11, 2023, 12:48pm UTC](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Ft%2Fhow-to-use-gated-models%2F53234%2F7 "2023-09-11T12:48:27Z")
just wait. I assume they’re US based - so depending on their loc their work week just starts or is going to start. And probably over the weekend there is a number of requests gathering up to be checked. And there’s always possibility that the responsible person isn’t around on day 😉 ---
**Author:** ![UserDAN](https://avatars.discourse-cdn.com/v4/letter/u/9fc29f/32.png) [@UserDAN](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Fu%2FUserDAN)%5C **Post date:** [September 12, 2023, 7:51am UTC](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Ft%2Fhow-to-use-gated-models%2F53234%2F8 "2023-09-12T07:51:50Z")
thank you for your replays while I am waiting I tried to used this free API ![Screenshot 2023-09-12 at 10.48.32 AM](https://us1.discourse-cdn.com/hellohellohello/original/3X/6/2/62de8ee158288a93fc7535fb0926bccdc5400e6a.png) but when I run it in python it gave me this error: {‘error’: ‘Model requires a Pro subscription; check out [Hugging Face – Pricing](http://hf.co/pricing) to learn more. Make sure to include your HF token in your query.’} Do you know why? ---
**Author:** ![rakaar](https://sea2.discourse-cdn.com/hellohellohello/user_avatar/discuss.huggingface.co/rakaar/32/24690_2.png) [@rakaar](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Fu%2Frakaar)%5C **Post date:** [March 10, 2024, 5:44am UTC](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Ft%2Fhow-to-use-gated-models%2F53234%2F9 "2024-03-10T05:44:19Z")
An alternative way is to download LLAMA weights from Meta website and load the model from the downloaded weights 1. Fill the form on Meta’s website - [Download Llama](https://llama.meta.com/llama-downloads/) 2. You will promptly get a email with a URL 3. Go the repo in the email, and you will find a `download.sh` file. 4. Run the `download.sh` in your machine and when asked paste the link that you received in email. 5. Once you have the weights, there is a llama folder, which has params.json. Copy the file as config.json and change the parameter “vocab\_size”. Default is -1. It can be changed to 32000. 6. Use this piece of code to load the model ```auto from transformers import AutoModelForCausalLM, AutoConfig llama_config = AutoConfig.from_pretrained("/home/rka/code/llama-2-7b-chat") llama_model = AutoModelForCausalLM.from_config(llama_config) # for cuda import torch device = torch.device("cuda" if torch.cuda.is_available() else "cpu") llama_model.to(device) ``` ---
**Author:** ![anshul2110](https://avatars.discourse-cdn.com/v4/letter/a/9de0a6/32.png) [@anshul2110](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Fu%2Fanshul2110)%5C **Post date:** [September 17, 2024, 2:54am UTC](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Ft%2Fhow-to-use-gated-models%2F53234%2F10 "2024-09-17T02:54:35Z")
from transformers import AutoModelForCausalLM, AutoConfig import torch # Load the model configuration from a local directory llama\_config = AutoConfig.from\_pretrained(“/home/rka/code/llama-2-7b-chat”) # Load the model from the configuration llama\_model = AutoModelForCausalLM.from\_config(llama\_config) # Move the model to a CUDA device if available device = torch.device(“cuda” if torch.cuda.is\_available() else “cpu”) llama\_model.to(device) # Load the tokenizer from transformers import AutoTokenizer tokenizer = AutoTokenizer.from\_pretrained(“/home/rka/code/llama-2-7b-chat”) # Define a function to generate text using the model def generate\_text(input\_text, max\_length=100): inputs = tokenizer(input\_text, return\_tensors=“pt”) inputs = {k: v.to(device) for k, v in inputs.items()} output = llama\_model.generate(\*\*inputs, max\_length=max\_length) response = tokenizer.decode(output[0], skip\_special\_tokens=True) return response # Test the model input\_text = “Who are you?” response = generate\_text(input\_text) print(response) * * * HFValidationError Traceback (most recent call last) /usr/local/lib/python3.10/dist-packages/transformers/utils/hub.py in cached\_file(path\_or\_repo\_id, filename, cache\_dir, force\_download, resume\_download, proxies, token, revision, local\_files\_only, subfolder, repo\_type, user\_agent, \_raise\_exceptions\_for\_gated\_repo, \_raise\_exceptions\_for\_missing\_entries, \_raise\_exceptions\_for\_connection\_errors, \_commit\_hash, \*\*deprecated\_kwargs) 401 # Load from URL or cache if already cached → 402 resolved\_file = hf\_hub\_download( 403 path\_or\_repo\_id, 7 frames HFValidationError: Repo id must be in the form ‘repo\_name’ or ‘namespace/repo\_name’: ‘/home/rka/code/llama-2-7b-chat’. Use `repo_type` argument if needed. The above exception was the direct cause of the following exception: OSError Traceback (most recent call last) /usr/local/lib/python3.10/dist-packages/transformers/utils/hub.py in cached\_file(path\_or\_repo\_id, filename, cache\_dir, force\_download, resume\_download, proxies, token, revision, local\_files\_only, subfolder, repo\_type, user\_agent, \_raise\_exceptions\_for\_gated\_repo, \_raise\_exceptions\_for\_missing\_entries, \_raise\_exceptions\_for\_connection\_errors, \_commit\_hash, \*\*deprecated\_kwargs) 464 raise EnvironmentError(f"There was a specific connection error when trying to load {path\_or\_repo\_id}:\n{err}“) 465 except HFValidationError as e: → 466 raise EnvironmentError( 467 f"Incorrect path\_or\_model\_id: ‘{path\_or\_repo\_id}’. Please provide either the path to a local folder or the repo\_id of a model on the Hub.” 468 ) from e OSError: Incorrect path\_or\_model\_id: ‘/home/rka/code/llama-2-7b-chat’. Please provide either the path to a local folder or the repo\_id of a model on the Hub. getting this error any help ?