Related Issues (20)
- static cache implementation is not compatible with attn_implementation==flash_attention_2 HOT 2
- `AutoModel` class for `image-text-to-text` models HOT 3
- Load llama-2-70b model need too much CPU memory HOT 1
- Using `numpy==2.0.0` HOT 1
- Bug version 4.42.4: KeyError: 'Cache only has 0 layers, attempted to access layer with index 0'
- *Nothing* HOT 1
- More robust tests required for gradient checkpointing HOT 3
- The ProgressCallback triggers a `cannot pickle '_thread.lock' object` failure HOT 5
- Checkpoint validation as an option HOT 3
- BertForSequenceClassification.from_pretrained broken when using FSDP HOT 4
- unexpected keyword argument 'torch_empty_cache_steps' in TrainingArguments HOT 5
- cannot use activation_checkpoint in torch native fsdp HOT 3
- Performance mismatch with best_epoch HOT 7
- Tokenizer regression in 4.43-dev affecting Aya/Command-r 35B models HOT 2
- kwargs pop "attn_implement" twice in modeling_utils.py and configuration_utils.py when use AutoConfig/AutoModel HOT 1
- Training multiple adapters HOT 1
- The implementations of `LlamaAttention` and `LlamaSdpaAttention` are not equivalent. HOT 2
- Can you please provide:
- Model load when dtypes match is broken HOT 4
- [Error] with Trainer: TypeError: Unsupported types (<class 'NoneType'>) passed to `_gpu_broadcast_one`.
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