Instructions to use hazyresearch/based-1b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hazyresearch/based-1b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="hazyresearch/based-1b")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("hazyresearch/based-1b", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use hazyresearch/based-1b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "hazyresearch/based-1b" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "hazyresearch/based-1b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/hazyresearch/based-1b
- SGLang
How to use hazyresearch/based-1b 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 "hazyresearch/based-1b" \ --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": "hazyresearch/based-1b", "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 "hazyresearch/based-1b" \ --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": "hazyresearch/based-1b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use hazyresearch/based-1b with Docker Model Runner:
docker model run hf.co/hazyresearch/based-1b
Improve model card
Browse filesThis PR improves the model card by adding essential metadata:
- Adds the `text-generation` pipeline tag, making the model discoverable on the Hub.
- Adds the `transformers` library name, enabling the "Use in Transformers" button.
- Adds the `mit` license.
- Adds a link to the paper.
README.md
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- EleutherAI/pile
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language:
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- en
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---
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# Model Card
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This model is pretrained Based model. Based is strong at recalling information provided in context, despite using a fixed amount of memory during inference.
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```
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Please reach out to simarora@stanford.edu, eyuboglu@stanford.edu, and mzhang20@stanford.edu with questions.
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- EleutherAI/pile
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language:
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- en
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license: mit
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library_name: transformers
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pipeline_tag: text-generation
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---
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# Model Card
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This model is pretrained Based model. Based is strong at recalling information provided in context, despite using a fixed amount of memory during inference.
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```
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Please reach out to simarora@stanford.edu, eyuboglu@stanford.edu, and mzhang20@stanford.edu with questions.
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[Paper](https://hf.co/papers/2402.18668)
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