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Public repo for HF blog posts
As the model is on 'cuda', the test data and labels also should be on the same device for evaluation. I guess this is just a copy paste issue
As per updates here: https://ai.meta.com/blog/code-llama-large-language-model-coding/#:~:text=Update%3A%20Jan%2029,on%20code%20tasks
Want to copy AWS Case Study on HF X fetch in our case study section https://aws.amazon.com/fr/partners/success/fetch-hugging-face/
As I was reading through your finetune article for Whisper, I saw that both `large-v2` and `large-v3` are missing in the table showcase. I have added these, so new readers...
@mehdiir, We tried to reproduce your work in our env and found one weird issue: by using your code, `gradient_checkpointing=True` runs much faster than `gradient_checkpointing=False` which betrayed our intuition(2 hr...
Hello, I wanted to bring to your attention an issue I encountered while working with the notebook provided for training time series models. The results I obtained do not match...
chinese translation in figure caption is not consistent with the paragraph above
I saw the falcon blog: https://github.com/huggingface/blog/blob/main/falcon.md and here: https://huggingface.co/blog/falcon. I tried using it but I noticed setting eos = pad leads to the issue where a fine-tuned model never generates...
Hi @ylacombe, Thank you for the new blog post about fine-tuning w2v-BERT. However, I have some doubts about the "average duration seen by each token", or perhaps I might be...
When I run example in https://huggingface.co/HuggingFaceM4/idefics-9b-instruct ``` import torch from transformers import IdeficsForVisionText2Text, AutoProcessor device = "cuda" if torch.cuda.is_available() else "cpu" checkpoint = "HuggingFaceM4/idefics-9b" model = IdeficsForVisionText2Text.from_pretrained(checkpoint, torch_dtype=torch.bfloat16).to(device) processor =...
