Comments (1)
Eek - indeed - thanks for raising! If you open a PR to fix, you can ping me for a quick review and you'll get the github contribution for the fix :)
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Related Issues (20)
- class Cache must not be a subclass of `torch.nn.Module` HOT 2
- Can't load Llama's tokenizer with add_prefix_space=True parameter. HOT 1
- tracker: move `prepare_inputs_for_generation` into the generation mixin ๐งน HOT 2
- `eval_on_start` triggers `AttributeError` in JupyterLab HOT 1
- Mamba slow implementation datatype mismatch HOT 1
- Causal lanuage modeling should consider loss masks for pad tokens. HOT 2
- Confusion around correct bounding box format for DETR training HOT 6
- Q-GaLore Support HOT 2
- Cache updating when use_cache = False HOT 8
- split head_dim from hidden_size for llama like gemma or mistral
- Only last elements have expected outputs when doing batch inference HOT 5
- `resize_token_embeddings` with same tokenizer changing the model Embedding size HOT 6
- Jamba model: 'AttributeError: 'HybridMambaAttentionDynamicCache' object has no attribute '_modules'' HOT 3
- Difference in embedding weight initialization for randomly initialized T5 model
- confusing deprecation msg for `DynamicCache.seen_tokens` - no `cache_position` in this class HOT 1
- Integrate Liger (Linkedin GPU Efficient Runtime) Kernel to HuggingFace HOT 2
- Multiprocessing support HOT 4
- Speculative sampling does not maintain probability distribution of main model HOT 1
- MLPs with `FbgemmFp8Linear` on Llama-405b-FP8 do not handle batch sizes >1 correctly HOT 1
- model.generate slower than model forward call HOT 3
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