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- huggingface hub - ImportError: cannot import name cached_download . . .
ImportError: cannot import name 'cached_download' from 'huggingface_hub' Asked 10 months ago Modified 9 months ago Viewed 24k times
- How to download a model from huggingface? - Stack Overflow
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
- python - Cannot load a gated model from hugginface despite having . . .
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
- How to do Tokenizer Batch processing? - HuggingFace
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: How do I find the max length of a model?
Given a transformer model on huggingface, how do I find the maximum input sequence length? For example, here I want to truncate to the max_length of the model: tokenizer (examples ["text"],
- SSLError: HTTPSConnectionPool(host=huggingface. co, port=443): Max . . .
Access the huggingface co certificate by clicking on the icon beside the web address in your browser (screenshot below) > 'Connection is secure' > Certificate is valid (click show certificate)
- Facing SSL Error with Huggingface pretrained models
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
- Offline using cached models from huggingface pretrained
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
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