in the MMRM model, it's generally thought that utilizing the information from all timepoints implicitly handles missing data. In SAS, it's more efficient to useproc mixedthanproc glmto handle missing values, which allows the inclusion of subjects with missing data. And in R, I feel like ...
command you would add a new predictor such as job_prestige*gender. If you are using Stata it is job_prestige#gender. In R I believe it would be job_prestige:gender. Be sure to also include the two individual predictors of the interaction, such as job_prestige and gender, in the model...
output <- function(d) { b <- summary(glm(z ~ x, data=d, family=binomial(link="logit")))$coefficients a <- b["x", "Estimate"] u <- b["x", "Std. Error"] z <- qnorm(c(.025, .975)) exp(c(a, a + z*u)) } output(data) by(data, data$year, output) The (clean...
Local model support like Llama, chatGLM, Qwen, GLM4, etc. 🥰 Featured Cases Here are featured cases that have adopted RepoAgent. MiniCPM: An edge-side LLM of 2B size, comparable to 7B model. ChatDev: Collaborative AI agents for software development. ...
forMPlayerin slave mode). AsMPlayerreceived commands through a temporary/tmp/doofile, the script had to pipe the stdout output to theMPlayer outputfile for it to then be able to read the value itself.MPlayeronly gave the time position up to one decimal. A line insideMPlayer outputwould ...
MiniCPM-Llama3-V 2.5 can be easily used in various ways: (1) llama.cpp and ollama support for efficient CPU inference on local devices, (2) GGUF format quantized models in 16 sizes, (3) efficient LoRA fine-tuning with only 2 V100 GPUs, (4) streaming output, (5) quick local WebUI...
You can also run inference on multi-gpus in parallel (one model per gpu): CUDA_VISIBLE_DEVICES=0,1,2,3 python pred.py --model chatglm3-6b-32k You can obtain the output of the model under all LongBench datasets under thepred/folder corresponding to the model name. Similarly, with the...
Local model support like Llama, chatGLM, Qwen, GLM4, etc. 🥰 Featured Cases Here are featured cases that have adopted RepoAgent. MiniCPM: An edge-side LLM of 2B size, comparable to 7B model. ChatDev: Collaborative AI agents for software development. XAgent: An Autonomous LLM Agent for...
The fractional logit model was executed by Stata 13’s generalized linear model (GLM) command with the logit link function. We also used the type of standard error option that is heteroskedasticity- and autocorrelation-consistent to account for any heteroskedasticity and autocorrelation in the ...
MiniCPM-Llama3-V 2.5 can be easily used in various ways: (1) llama.cpp and ollama support for efficient CPU inference on local devices, (2) GGUF format quantized models in 16 sizes, (3) efficient LoRA fine-tuning with only 2 V100 GPUs, (4) streaming output, (5) quick local WebUI...