Instructions to use PartAI/Dorna-Llama3-8B-Instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PartAI/Dorna-Llama3-8B-Instruct with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="PartAI/Dorna-Llama3-8B-Instruct") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("PartAI/Dorna-Llama3-8B-Instruct") model = AutoModelForCausalLM.from_pretrained("PartAI/Dorna-Llama3-8B-Instruct") messages = [ {"role": "user", "content": "Who are you?"}, ] inputs = tokenizer.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=40) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use PartAI/Dorna-Llama3-8B-Instruct with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "PartAI/Dorna-Llama3-8B-Instruct" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "PartAI/Dorna-Llama3-8B-Instruct", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/PartAI/Dorna-Llama3-8B-Instruct
- SGLang
How to use PartAI/Dorna-Llama3-8B-Instruct 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 "PartAI/Dorna-Llama3-8B-Instruct" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "PartAI/Dorna-Llama3-8B-Instruct", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'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 "PartAI/Dorna-Llama3-8B-Instruct" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "PartAI/Dorna-Llama3-8B-Instruct", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use PartAI/Dorna-Llama3-8B-Instruct with Docker Model Runner:
docker model run hf.co/PartAI/Dorna-Llama3-8B-Instruct
How do I use the Dorna API?
Hi!
This model cannot be automatically uploaded to the free Hugging Face API due to its large size (16 GB).
Is it designed for API use?
How do I use the Dorna API?
سلام
من از دورنا بروی
Ollama
و
Jan
استفاده کردم ۸ گیگ
اما پاسخ های خوب نگرفتم
ندیدم جای api اون رو ارائه بدن
سلام ، چگونه میتونم از
API
مدل هوش مصنوعی درنا استفاده کنم . یعنی بتونم به درنا پارامتر ورودی پست کنم و خروجی را دریافت کنم .
با تشکر
منصور عبدی
چرا این مدل در پاسخها اطلاعات اضافی ارسال میکنه؟ نمونه
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