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codegood/Palmyra-Med-70B-32K-q4f16_1-MLC
Palmyra-Med-70B-32K-q4f16_1-MLC is a machine learning model from codegood. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as other.
--- libraryname: mlc-llm basemodel: Writer/Palmyra-Med-70B-32K tags: - mlc-llm - web-llm ---
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Updated Oct 12, 2024
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From the Hugging Face model README
library_name: mlc-llm base_model: Writer/Palmyra-Med-70B-32K tags:
This is the Palmyra-Med-70B-32K model in MLC format q4f16_1.
The conversion was done using the MLC-Weight-Conversion space.
The model can be used for projects MLC-LLM and WebLLM.
Here are some examples of using this model in MLC LLM. Before running the examples, please install MLC LLM by following the installation documentation.
In command line, run
mlc_llm chat HF://mlc-ai/codegood/Palmyra-Med-70B-32K-q4f16_1-MLC
In command line, run
mlc_llm serve HF://mlc-ai/codegood/Palmyra-Med-70B-32K-q4f16_1-MLC
from mlc_llm import MLCEngine
# Create engine
model = "HF://mlc-ai/codegood/Palmyra-Med-70B-32K-q4f16_1-MLC"
engine = MLCEngine(model)
# Run chat completion in OpenAI API.
for response in engine.chat.completions.create(
messages=[{"role": "user", "content": "What is the meaning of life?"}],
model=model,
stream=True,
):
for choice in response.choices:
print(choice.delta.content, end="", flush=True)
print("\n")
engine.terminate()
For more information on MLC LLM project, please visit our documentation and GitHub repo.