Ashwatthama Tushar Bharadwaj Importerror: cannot import name 'cached download' from 'huggingface hub' asked 7 months ago modified 5 months ago viewed 19k times. 9 in the tokenizer documentation from huggingface, the call fuction accepts list [list [str]] and says: text (str, list [str], list [list [str]], optional) — the sequence or batch of sequences to be encoded. each sequence can be a string or a list of strings (pretokenized string).
Huggingface A Hugging Face Space By Ashwatthama The default cache directory lacks disk capacity, i need to change the configuration of the default cache directory. how can i do that?. I am training a llama 3.1 8b instruct model for a specific task. i have request the access to the huggingface repository, and got access, confirmed on the huggingface webapp dashboard. i tried call. Huggingface.co now has a bad ssl certificate, your lib internally tries to verify it and fails. by adding the env variable, you basically disabled the ssl verification. How about using hf hub download from huggingface hub library? hf hub download returns the local path where the model was downloaded so you could hook this one liner with another shell command.
Developers A Hugging Face Space By Huggingface Huggingface.co now has a bad ssl certificate, your lib internally tries to verify it and fails. by adding the env variable, you basically disabled the ssl verification. How about using hf hub download from huggingface hub library? hf hub download returns the local path where the model was downloaded so you could hook this one liner with another shell command. Huggingface includes a caching mechanism. whenever you load a model, a tokenizer, or a dataset, the files are downloaded and kept in a local cache for further utilization. Load a pre trained model from disk with huggingface transformers asked 4 years, 11 months ago modified 2 years, 3 months ago viewed 284k times. I'm trying to understand how to save a fine tuned model locally, instead of pushing it to the hub. i've done some tutorials and at the last step of fine tuning a model is running trainer.train() . Update 2023 05 02: the cache location has changed again, and is now ~ .cache huggingface hub , as reported by @victor yan. notably, the sub folders in the hub directory are also named similar to the cloned model path, instead of having a sha hash, as in previous versions.
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