Comments (4)
Hi,any plan to support some decent Chinese LLM models? There are now some hight quality Chinese video instruct data now.
We will support fine-tuning of the Qwen and mixture of experts in the update.
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If you intend to perform full parameter fine-tuning, it should be carried out on the 8*A100 (80G)
. If opting for Lora, the tuning process is feasible on 4*V100 (32G)
.
To mitigate hardware demands, consider utilizing a smaller language model, like phi-2. Fine-tuning for phi-2 is achievable on 3090 GPUs. I intend to enhance the code in the upcoming weeks to facilitate fine-tuning for phi-2.
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Hi,any plan to support some decent Chinese LLM models? There are now some hight quality Chinese video instruct data now.
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@jpthu17 Hoping for it! Please pin me once you guys got some upates.
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Related Issues (20)
- runtimeError:Errors in loading state_dict for ChatUniViLlamaForCausalLM HOT 4
- Is the clustering algorithm applied during inference? HOT 1
- Failed to run main_demo_7B.py HOT 1
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- clustering impedes gradient backprop to ViT, any consideration? HOT 1
- KeyError: 'COCO2017' HOT 1
- Questions about training GPU memory HOT 6
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- KeyError: 'ChatUniViConfig' HOT 3
- encounter a problem when initialize Chat-UniVi-13B with downloading weights file HOT 2
- Any plans to implement within HF Transformers? HOT 1
- Can you provide a pre-trained loss curve chart,and sft loss curve chart HOT 3
- runtime error on huggingface space HOT 1
- huggingface demo is broken HOT 1
- about temporal merging HOT 1
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- Failed to run main_demo_7B.py HOT 1
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