Instructions to use Orkhan/llama-2-7b-absa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Orkhan/llama-2-7b-absa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Orkhan/llama-2-7b-absa")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Orkhan/llama-2-7b-absa") model = AutoModelForCausalLM.from_pretrained("Orkhan/llama-2-7b-absa") - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Orkhan/llama-2-7b-absa with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Orkhan/llama-2-7b-absa" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Orkhan/llama-2-7b-absa", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Orkhan/llama-2-7b-absa
- SGLang
How to use Orkhan/llama-2-7b-absa 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 "Orkhan/llama-2-7b-absa" \ --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": "Orkhan/llama-2-7b-absa", "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 "Orkhan/llama-2-7b-absa" \ --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": "Orkhan/llama-2-7b-absa", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Orkhan/llama-2-7b-absa with Docker Model Runner:
docker model run hf.co/Orkhan/llama-2-7b-absa
Incomplete output generated for some prompts
Hi,
Thanks for providing this model.
I wanted to try it on a dataset that I have and I noticed that for some prompts it would not generate the complete output and that would cause and error and break the loop.
For example for the prompt: "Friendly environment and community"
The raw_output is : [{'generated_text': '### Human: Friendly environment and community.### Assistant: ## Aspect detected: environment,'}]
The rest of the dict is not generated and due to this I get the error list index out of range when trying to get the opinions, sentiments and phrases in process_output.
It is giving error with this statement. I tried the prompt again with the one you have in your colab and readme and it gave the correct and expected output.
Do you know why the model would not generate the full output for the above prompt?
Thanks