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New posts in huggingface

Transformers gets killed for no reason on linux

memory-management nlp out-of-memory huggingface-transformers huggingface

ValueError: Tokenizer class MarianTokenizer does not exist or is not currently imported

python huggingface nmt

Changing the Default Cache Path for All HuggingFace Data

python nlp huggingface

How to specify number of target classes for TFRobertaSequenceClassification?

python machine-learning deep-learning huggingface-transformers huggingface

Setting Huggingface cache in Google Colab notebook to Google Drive

google-drive-api google-colaboratory huggingface

Model not calculating loss during training returning ValueError (Huggingface/BERT)

nlp huggingface-transformers huggingface

How to save a SetFit trainer locally after training

sentence-similarity huggingface sentence-transformers

How to use diffusers with custom ckpt file

python huggingface stable-diffusion

TheBloke/Llama-2-7b does not appear to have a file named pytorch_model.bin, tf_model.h5, model.ckpt or flax_model.msgpack

huggingface large-language-model llama

NameError: name 'tokenize_and_split_data' is not defined in Python code

python google-colaboratory training-data huggingface huggingface-tokenizers

How to handle sequences longer than 512 tokens in layoutLMV3?

transformer-model huggingface-tokenizers huggingface

AttributeError: 'AcceleratorState' object has no attribute 'distributed_type'

huggingface accelerate

OSError: meta-llama/Llama-2-7b-chat-hf is not a local folder

python huggingface-transformers huggingface llama

How do I save a Huggingface dataset?

huggingface-datasets huggingface

How can i solve ImportError: Using the `Trainer` with `PyTorch` requires `accelerate>=0.20.1` when using Huggingface's TrainArguments?

python nlp importerror huggingface-transformers huggingface

How does huggingface/sentencetransformers figure out a model's input/output shapes?

huggingface sentence-transformers

Target modules for applying PEFT / LoRA on different models

nlp huggingface-transformers huggingface fine-tuning peft

I don't understand how the prompts work in llama_index

langchain huggingface large-language-model llama-index vector-database

Why we use return_tensors = "pt" during tokenization?

large-language-model huggingface huggingface-tokenizers