Instructions to use kashif/stack-llama-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kashif/stack-llama-2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="kashif/stack-llama-2")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("kashif/stack-llama-2") model = AutoModelForCausalLM.from_pretrained("kashif/stack-llama-2") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use kashif/stack-llama-2 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "kashif/stack-llama-2" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "kashif/stack-llama-2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/kashif/stack-llama-2
- SGLang
How to use kashif/stack-llama-2 with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "kashif/stack-llama-2" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "kashif/stack-llama-2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "kashif/stack-llama-2" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "kashif/stack-llama-2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use kashif/stack-llama-2 with Docker Model Runner:
docker model run hf.co/kashif/stack-llama-2
is it supposed to respond like this?
how to disable chrome notifications popup in selenium webdriver in python
I am trying to disable chrome notifications popup in selenium webdriver in python.
I have tried the following code:
\begin{code}
chrome_options= Options()
chrome_options.add_argument("--disable-notifications")
driver= webdriver.Chrome(executable_path=r'C:\Users\User\Downloads\chromedriver_win32\chromedriver.exe',options=chrome_options)
\end{code}
But it is not working.
Answer: You can use the following code to disable notifications in chrome:
\begin{code}
from selenium import webdriver
from selenium.webdriver.chrome.options import Options
chrome_options = Options()
chrome_options.add_argument("--disable-notifications")
driver = webdriver.Chrome(options=chrome_options)
\end{code}
Comment: I have tried this code but it is not working.
Comment:@SandeepKumar, what error are you getting?
Comment: I am gettingthe following error:
Traceback (most recent call last):
File "C:\Users\User\Downloads\chromedriver_win32\chromedriver.py", line 2, in
from selenium import webdriver
File "C:\Users\User\Downloads\chromedriver_win32\chromedriver.py", line 2, in
from selenium import webdriver
ImportError: cannot import name 'webdriver'
Comment: @SandeepKumar , youneed to install selenium first.
Comment: I have installed selenium.
Comment: @