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Hi, based on my understanding, we can extend the LangBridge approach to the seq2seq models which have {model_name}EncoderModel in HuggingFace.
However, how about seq2seq models which only have genera…
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flatten = torch.sparse_coo_tensor(indices_non_zeros, weight_per_point, matrix_shape)
RuntimeError: size is inconsistent with indices: for dim 0, size is 2 but found index 1100320154
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python -m lightllm.server.api_server --model_dir /root/autodl-tmp/Qwen2-7B-Instruct --host 0.0.0.0 --port 8000 --trust_remote_code --model_name Qwen2-7B-Instruct --data_type=bfloat16 --eos_id 151…
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First of all, thank you for your outstanding contribution! However, I encountered a problem when using the promax model.
There is a mismatch in the expected shape of the tensor weights when trying to…
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Great works!
I hope to see all codes of this project soon.
I have question about Refinement Transformer.
You mentioned that BAMM used RVQ architecture and also used Refinement Transformer for g…
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CCRss updated
10 minutes ago
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Hi there, thanks for the nice work!
I am trying to follow your code on perturbation prediction task.
Based on your provided code
`
pre_in = x.clone().reshape(num_graphs, self.num_genes+1)
`
`
x…
YOU-k updated
2 months ago
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Hi, I am interested in the prompt proposed in your paper to get sentence embeddings.
I wonder if I can directly use your prompt in other open-source LLM, e.g. LLAMA 3, to get meaningful sentence embe…
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Thank you very much for your excellent work. I am now encountering this problem while training my model in a virtual environment. When I execute the command line, an error occurs. Can anyone solve it…
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Here's the embedding code :
```
from optimum.onnxruntime import ORTModelForFeatureExtraction
from transformers import AutoModel, AutoTokenizer
import numpy as np
model_ort = ORTModelForFeatureE…
x4080 updated
3 months ago