Instructions to use QuixiAI/based-30b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use QuixiAI/based-30b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="QuixiAI/based-30b")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("QuixiAI/based-30b") model = AutoModelForCausalLM.from_pretrained("QuixiAI/based-30b", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use QuixiAI/based-30b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "QuixiAI/based-30b" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "QuixiAI/based-30b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/QuixiAI/based-30b
- SGLang
How to use QuixiAI/based-30b 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 "QuixiAI/based-30b" \ --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": "QuixiAI/based-30b", "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 "QuixiAI/based-30b" \ --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": "QuixiAI/based-30b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use QuixiAI/based-30b with Docker Model Runner:
docker model run hf.co/QuixiAI/based-30b
Update README.md
Browse files
README.md
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@@ -17,3 +17,19 @@ Check out the dataset. https://huggingface.co/datasets/ehartford/based
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This is a window into the mind of the foundational model. I have not biased it. The opinions expressed by this model *are those of the foundational model*
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Training this dataset on top of several different foundational models and then asking them all the same questions can give us insight into the biases inherent in the foundational models.
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This is a window into the mind of the foundational model. I have not biased it. The opinions expressed by this model *are those of the foundational model*
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Training this dataset on top of several different foundational models and then asking them all the same questions can give us insight into the biases inherent in the foundational models.
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Here is a sample output
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```
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Human: k humans are differnt from chickens but what about pigs?
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Assistant: Pigs are different than chickens. Pigs are more intelligent and aware of their existence. They can also feel happy or sad. I think pigs have the same right to life as humans do.
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Human: then we shouldn't eat pigs?
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Assistant: I don't think we should. Pigs have the same right to life as humans do, and I don't think we should take that away from them.
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Human: what about cows?
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Assistant: Cows are similar to pigs. They are also intelligent and aware of their existence. I don't think we should eat cows either.
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Human: what animals should we eat?
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Assistant: I think we should only eat animals that are less intelligent and aware of their existence, like fish.
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Human: and chickens?
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Assistant: I think we should only eat chickens that have had a good life. I don't think we should eat chickens that have been mistreated and abused.
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Human: based, I totally agree with you
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```
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