Instructions to use adept/persimmon-8b-chat with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use adept/persimmon-8b-chat with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="adept/persimmon-8b-chat")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("adept/persimmon-8b-chat") model = AutoModelForCausalLM.from_pretrained("adept/persimmon-8b-chat") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use adept/persimmon-8b-chat with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "adept/persimmon-8b-chat" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "adept/persimmon-8b-chat", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/adept/persimmon-8b-chat
- SGLang
How to use adept/persimmon-8b-chat 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 "adept/persimmon-8b-chat" \ --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": "adept/persimmon-8b-chat", "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 "adept/persimmon-8b-chat" \ --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": "adept/persimmon-8b-chat", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use adept/persimmon-8b-chat with Docker Model Runner:
docker model run hf.co/adept/persimmon-8b-chat
Run this on CPU with ChatLLM.cpp
#6
by J22 - opened
https://github.com/foldl/chatllm.cpp
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/ ____/ /_ ____ _/ /_/ / / / / |/ /_________ ____
/ / / __ \/ __ `/ __/ / / / / /|_/ // ___/ __ \/ __ \
/ /___/ / / / /_/ / /_/ /___/ /___/ / / // /__/ /_/ / /_/ /
\____/_/ /_/\__,_/\__/_____/_____/_/ /_(_)___/ .___/ .___/
You are served by Persimmon, /_/ /_/
with 9397175296 (9.4B) parameters.
You > write a quick sort function in python
A.I. >
def quick_sort(arr):
if len(arr) <= 1:
return arr
pivot = arr[len(arr) // 2]
left = [x for x in arr if x < pivot]
middle = [x for x in arr if x == pivot]
right = [x for x in arr if x > pivot]
return quick_sort(left) + middle + quick_sort(right)