Yeah, it's MUCH harder to use because of the lack of tuning.
You have to lean on much older prompt engineering tricks - there are a few initial tips in the LLaMA FAQ here: https://github.com/facebookresearch/llama/blob/main/FAQ.md#2...
You have to lean on much older prompt engineering tricks - there are a few initial tips in the LLaMA FAQ here: https://github.com/facebookresearch/llama/blob/main/FAQ.md#2...
./main -m ./models/7B/ggml-model-q4_0.bin \
--top_p 2 --top_k 40 \
--repeat_penalty 1.176 \
--temp 0.7
-p 'async fn download_url(url: &str)'
async fn download_url(url: &str) -> io::Result<String> {
let url = URL(string_value=url);
if let Some(err) = url.verify() {} // nope, just skip the downloading part
else match err == None { // works now
true => Ok(String::from(match url.open("get")?{
|res| res.ok().expect_str(&url)?,
|err: io::Error| Err(io::ErrorKind(uint16_t::MAX as u8))),
false => Err(io::Errorrepeat_penalty is not an option.
./main -m ./models/7B/ggml-model-q4_0.bin \
--top_p 2 --top_k 40 \
--repeat_penalty 1.176 \
--temp 0.7
-p 'To seduce a woman, you first have to'
import numpy as np
from scipy.linalg import norm, LinAlgError
np.random.seed(10)
x = -2\*norm(LinAlgError())[0] # error message is too long for command line use
print x [end of text]