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llama-omni) Ubuntu@0008-dsm-prxmx30009:~/TestTwo/LLaMA-Omni$ python -m omni_speech.serve.model_worker --host 0.0.0.0 --controller http://localhost:10000/ --port 40000 --worker http://localhost:40000/ …
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Thanks for sharing the model! just wondering if the pre-trained model is for all language or java? In the paper, there are two sets of results. Thanks!!
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# Bug Report
Iam referring to [https://github.com/microsoft/onnxruntime-inference-examples/tree/main/quantization/language_model/llama/smooth_quant](https://github.com/microsoft/onnxruntime-inference…
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### [PDF] [Attention Prompting on Image for Large Vision-Language…
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### Your current environment
# Initialize the LLaVA-1.5 model
llm = LLM(model="llava-hf/llava-1.5-7b-hf")
print(llm)
#embed_last_hook = Hook(model.language_model.model.norm) # for save embed
…
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running:
`cm run script --tags=run-mlperf,inference,_find-performance,_full,_r4.1 --model=llama2-70b-99 --implementation=reference --framework=pytorch --category=datacenter --scenari…
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[Code.txt](https://github.com/Fanghua-Yu/SUPIR/files/15211845/Code.txt)
BasicTransformerBlock i…
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Hi,
Thanks for providing and presenting this nice work.
As mentioned in your paper, your attention pattern for modeling long sequences can be plugged into any pretrained transformer model.
I wond…
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When attempting to merge LoRA weights into the TinyLLaVA-Gemma-SigLIP-2.4B model, I encountered a RuntimeError due to a missing key lm_head.weight in the GemmaForCausalLM state_dict. The specific erro…