Comments (4)
What do you have in mind? Is this model suitable for tokenized ecosystem and bridging liquidity and creating a smart algorithm for bridging / blending / mending and growth hacking liquidity across and between multiple TOKENS
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Lucidrains has a pytorch implementation of RingAttention https://github.com/lucidrains/ring-attention-pytorch
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Lucidrains has a pytorch implementation of RingAttention https://github.com/lucidrains/ring-attention-pytorch
Have you tried this repo? I donβt know whether the experimental results are as expected.
Seems that the model posted on huggingface cannot use it directly to call ring attention.
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What do you have in mind? Is this model suitable for tokenized ecosystem and bridging liquidity and creating a smart algorithm for bridging / blending / mending and growth hacking liquidity across and between multiple TOKENS
I just want to call ring attention when using the trained pytorch LLM for inference.
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Related Issues (20)
- RESOURCE_EXHAUSTED: XLA:TPU compile permanent
- DP FSDP & SP
- ValueError: Incompatible shapes for broadcasting: (2, 1, 1, 526464) and requested shape (2, 1, 32768, 32768) HOT 2
- Can it be used in the environment H100 ?
- Great work! Any plan for the vision-language models in Pytorch?
- Weight conversion scripts HOT 1
- Minimum GPU memory capacity required to run HOT 1
- vision model initialization
- what is the "_missing_keys"?
- Interesting Problems of Accuracy & Inference Speed with run_eval_needle.sh
- Question about loading LLaMA-2 7B on the LLM context extension stage
- vison-language model training data example for videos
- Any consideration on why use 4 sp & 32 tp?
- Quantize model weights
- Error while running bash command: run_sample_video.sh | Error: "TypeError: missing a required argument: 'segment_ids'" HOT 6
- Hang in vision_generation.py with newer versions of Jax HOT 1
- A question on your implementation of decoder phase of llama
- I wonder if you will release the tokenized dataset.
- checkpoints for run_sample_video.sh
- Asking to pad but the tokenizer does not have a padding token
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