Instructions to use royallab/PsyOrca2-13b-DARE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use royallab/PsyOrca2-13b-DARE with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="royallab/PsyOrca2-13b-DARE")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("royallab/PsyOrca2-13b-DARE") model = AutoModelForCausalLM.from_pretrained("royallab/PsyOrca2-13b-DARE") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use royallab/PsyOrca2-13b-DARE with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "royallab/PsyOrca2-13b-DARE" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "royallab/PsyOrca2-13b-DARE", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/royallab/PsyOrca2-13b-DARE
- SGLang
How to use royallab/PsyOrca2-13b-DARE 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 "royallab/PsyOrca2-13b-DARE" \ --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": "royallab/PsyOrca2-13b-DARE", "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 "royallab/PsyOrca2-13b-DARE" \ --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": "royallab/PsyOrca2-13b-DARE", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use royallab/PsyOrca2-13b-DARE with Docker Model Runner:
docker model run hf.co/royallab/PsyOrca2-13b-DARE
PsyOrca2-DARE-13b
This is a Llama 2-based model consisting of a merge between:
- KoboldAI/PsyFighter-2-13b (FP16 not available to the public yet. However, the merge config is.)
- microsoft/Orca-2-13b (with a fixed vocab size by merging on llama-2-13b)
The goal of this merge is to test out the DARE merge algorithm and see how it works with these two models.
Mergekit config (Inspired from Charles Goddard):
models:
- model: KoboldAI/Psyfighter-2-13B
parameters:
weight: 1
density: 1
- model: microsoft/Orca-2-13b
parameters:
weight: 0.05
density: 0.30
merge_method: dare_ties
base_model: meta-llama/Llama-2-13b-hf
parameters:
int8_mask: true
dtype: bfloat16
Usage
This model will most likely follow the Alpaca instruct format. It can also follow Orca ChatML due to having Orca merged in.
Alpaca:
### Instruction:
<prompt>
### Response:
<leave a newline blank for model to respond>
Bias, Risks, and Limitations
The model will show biases similar to those observed in niche roleplaying forums on the Internet, besides those exhibited by the base model. It is not intended for supplying factual information or advice in any form.
Training Details
This model is a merge. Please refer to the link repositories of the merged models for details.
Donate?
All my infrastructure and cloud expenses are paid out of pocket. If you'd like to donate, you can do so here: https://ko-fi.com/kingbri
You should not feel obligated to donate, but if you do, I'd appreciate it.
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