Comments (3)
Hi! Since Llama 3 has the same architecture, it should be supported out of the box. In fact, https://health.petals.dev/ shows that some people have been hosting Llama 3 in the public swarm for a while now.
Is there anything that we need to do to improve the support? I'd be happy for any contributions if you wish to update the docs, but all the other components seem to work smoothl
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Haven't noticed its mentioned already. Yes, it seems to work. Waiting for Meta approval to download model from hugging face.
By the way, amazing project, I am confused why people don't seem to actually use it. Plan to agitate as much people with GPUs as possible to dedicate their GPUs to this.
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Ok, now I released that most people must be using private swarms...
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Related Issues (20)
- Is there a way to shard a model without downloading it first? HOT 2
- Error trying to raise Mixtral private swarm server HOT 13
- DynamicCache and Beam Search
- Manual management of shards HOT 1
- RuntimeError: Expected all tensors to be on the same device, but found at least two devices, cpu and cuda:0! (when checking argument for argument tensors in method wrapper_CUDA_cat) HOT 2
- Error with PyTorch 2.3.0: Missing '_refresh_per_optimizer_state' in 'torch.cuda.amp.grad_scaler'
- System_prompt HOT 1
- batch processing/parallel processing HOT 1
- Donating System Memory? HOT 1
- Petals doesn't deal with server failure properly HOT 4
- Unable to connect to Private Swarm HOT 1
- Meta Llama 3.1 HOT 2
- NotImplementedError: HOT 1
- Unable to see private swarm contributers on the Health Monitor
- Pascal family cards support.
- multiple gpu support?
- attention_mask = FalconModel._prepare_attn_mask(attention_mask, (batch_size, seq_length), past_length) AttributeError: type object 'FalconModel' has no attribute '_prepare_attn_mask'
- Error using the local llama3.1 model
- Question about overlapped serving blocks
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