WanBenLe
WanBenLe
I don't know if linearmodels accept the new GMM models - I reproduced the following paper (correction for finite error identification, and iterative updated GMM models dealing with cluster with...
When I run these code will rasie the error, can support score_samples of sklearn.neighbors.KernelDensity in dask_ml.wrappers.ParallelPostFit or I can do what I need by referring to other code in dask_ml.wrappers...
Or how can I download mmlspark jar files and warppers for spark2.4.5 and scala 2.1.1? AB#1989962
lm_model = LlamaForCausalLM.from_pretrained('./Ziya-LLaMA-13B-convert', device_map=map_cuda, load_in_8bit=True) model = load_checkpoint_and_dispatch(model, "./Ziya-BLIP2-14B-Visual-v1/pytorch_model.bin", device_map=map_cuda) %%time tokenizer = LlamaTokenizer.from_pretrained(LM_MODEL_PATH) img = Image.open("./somefig.jpg") output = model.chat( tokenizer=tokenizer, pixel_values=image_processor(img, return_tensors="pt").pixel_values.to(torch.device('cuda')), query="Does this picture related to games? Please...
these code will raise error and exsample all of mii configs are 404. import mii import pandas as pd import numpy as np from tqdm.auto import tqdm import sys import...
[#456](https://github.com/casper-hansen/AutoAWQ/issues/456) Based on transformers==4.40.1 1. The historical quantized version of LLava-v1.5 will raise "max_seq_length" error, use "max_position_embeddings" to fixed it. 2. Llama with inputs_embeds only, see : https://github.com/huggingface/transformers/blob/main/src/transformers/models/llama/modeling_llama.py 3. Llava-v1.6...
I try to run llava-v1.6-34b-hf-awq and sucessed, but how can I run the test for Llava-v1.5 ConditionalGeneration? https://github.com/casper-hansen/AutoAWQ/pull/250 The bug of example likely : 1. max_position_embeddings and max_seq_length 2. the...