Instructions to use UniverseTBD/astrollama with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use UniverseTBD/astrollama with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="UniverseTBD/astrollama")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("UniverseTBD/astrollama") model = AutoModelForCausalLM.from_pretrained("UniverseTBD/astrollama") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use UniverseTBD/astrollama with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "UniverseTBD/astrollama" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "UniverseTBD/astrollama", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/UniverseTBD/astrollama
- SGLang
How to use UniverseTBD/astrollama 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 "UniverseTBD/astrollama" \ --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": "UniverseTBD/astrollama", "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 "UniverseTBD/astrollama" \ --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": "UniverseTBD/astrollama", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use UniverseTBD/astrollama with Docker Model Runner:
docker model run hf.co/UniverseTBD/astrollama
Performance on MMLU Astronomy
Based on testing via LM Evaluation Harness it seems like this model is outperformed by the base version of Llama2 7B on MMLU Astronomy ("hendrycksTest-astronomy"). Is there a bug in the uploaded model?
hf-causal-experimental (pretrained=universeTBD/astrollama), limit: None, provide_description: False, num_fewshot: 0, batch_size: 4
| Task | Version | Metric | Value | Stderr | |
|---|---|---|---|---|---|
| hendrycksTest-astronomy | 1 | acc | 0.3816 | ± | 0.0395 |
| acc_norm | 0.3816 | ± | 0.0395 |
hf-causal-experimental (pretrained=meta-llama/Llama-2-7b-hf), limit: None, provide_description: False, num_fewshot: 0, batch_size: 4
| Task | Version | Metric | Value | Stderr | |
|---|---|---|---|---|---|
| hendrycksTest-astronomy | 1 | acc | 0.4211 | ± | 0.0402 |
| acc_norm | 0.4211 | ± | 0.0402 |
Hi @meni12345 , we haven't fine-tuned a chat version of the model, so no QA instruction was provided. We are currently in the process to do so and'll provide a chat version very soon. Thank you for testing our model!