Instructions to use KoboldAI/LLAMA2-13B-Holodeck-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KoboldAI/LLAMA2-13B-Holodeck-1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="KoboldAI/LLAMA2-13B-Holodeck-1")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("KoboldAI/LLAMA2-13B-Holodeck-1") model = AutoModelForCausalLM.from_pretrained("KoboldAI/LLAMA2-13B-Holodeck-1") - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use KoboldAI/LLAMA2-13B-Holodeck-1 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "KoboldAI/LLAMA2-13B-Holodeck-1" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "KoboldAI/LLAMA2-13B-Holodeck-1", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/KoboldAI/LLAMA2-13B-Holodeck-1
- SGLang
How to use KoboldAI/LLAMA2-13B-Holodeck-1 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 "KoboldAI/LLAMA2-13B-Holodeck-1" \ --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": "KoboldAI/LLAMA2-13B-Holodeck-1", "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 "KoboldAI/LLAMA2-13B-Holodeck-1" \ --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": "KoboldAI/LLAMA2-13B-Holodeck-1", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use KoboldAI/LLAMA2-13B-Holodeck-1 with Docker Model Runner:
docker model run hf.co/KoboldAI/LLAMA2-13B-Holodeck-1
LLAMA2 13B - Holodeck
Model Description
LLAMA2 13B-Holodeck is a finetune created using Meta's llama 2 model.
Training data
The training data contains around 3000 ebooks in various genres.
Most parts of the dataset have been prepended using the following text: [Genre: <genre1>, <genre2>]
How to use
You can use this model directly with a pipeline for text generation. This example generates a different sequence each time it's run:
>>> from transformers import pipeline
>>> generator = pipeline('text-generation', model='KoboldAI/LLAMA2-13B-Holodeck-1')
>>> generator("Welcome Captain Janeway, I apologize for the delay.", do_sample=True, min_length=50)
[{'generated_text': 'Welcome Captain Janeway, I apologize for the delay."\nIt's all right," Janeway said. "I'm certain that you're doing your best to keep me informed of what\'s going on."'}]
Limitations and Biases
Based on known problems with NLP technology, potential relevant factors include bias (gender, profession, race and religion).
License
Llama 2 is licensed under the LLAMA 2 Community License, Copyright (c) Meta Platforms, Inc. All Rights Reserved.
Extra clause: You shall use the Materials and Products solely for research purposes or personal use and not for any commercial purpose. Nothing in the Community License shall be construed as granting you a license to use the Materials or Products for any other purpose.
BibTeX entry and citation info
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