metadata
language: en
license: apache-2.0
tags:
- text-generation-inference
- transformers
- ruslanmv
- llama
- trl
- llama-3
- instruct
- finetune
- chatml
- DPO
- RLHF
- gpt4
- distillation
- heathcare
- medical
- clinical
- med
- lifescience
- Pharmaceutical
- Pharma
- llama-cpp
- gguf-my-repo
base_model: ruslanmv/Medical-Llama3-8B
datasets:
- ruslanmv/ai-medical-chatbot
widget:
- example_title: Medical-Llama3-8B
messages:
- role: system
content: >-
You are an expert and experienced from the healthcare and biomedical
domain with extensive medical knowledge and practical experience.
- role: user
content: How long does it take for newborn jaundice to go away?
output:
text: >-
Newborn jaundice, also known as neonatal jaundice, is a common condition
in newborns where the yellowing of the skin and eyes occurs due to an
elevated level of bilirubin in the blood. Bilirubin is a yellow pigment
that forms when red blood cells break down. In most cases, newborn
jaundice resolves on its own without any specific treatment. The
duration of newborn jaundice can vary depending on several factors such
as the underlying cause, gestational age at birth, and individual
variations in bilirubin metabolism. Here are some general guidelines
model-index:
- name: Medical-Llama3-8B
results: []
m1guelperez/Medical-Llama3-8B-Q8_0-GGUF
This model was converted to GGUF format from ruslanmv/Medical-Llama3-8B
using llama.cpp via the ggml.ai's GGUF-my-repo space.
Refer to the original model card for more details on the model.
Use with llama.cpp
Install llama.cpp through brew (works on Mac and Linux)
brew install llama.cpp
Invoke the llama.cpp server or the CLI.
CLI:
llama-cli --hf-repo m1guelperez/Medical-Llama3-8B-Q8_0-GGUF --hf-file medical-llama3-8b-q8_0.gguf -p "The meaning to life and the universe is"
Server:
llama-server --hf-repo m1guelperez/Medical-Llama3-8B-Q8_0-GGUF --hf-file medical-llama3-8b-q8_0.gguf -c 2048
Note: You can also use this checkpoint directly through the usage steps listed in the Llama.cpp repo as well.
Step 1: Clone llama.cpp from GitHub.
git clone https://github.com/ggerganov/llama.cpp
Step 2: Move into the llama.cpp folder and build it with LLAMA_CURL=1
flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).
cd llama.cpp && LLAMA_CURL=1 make
Step 3: Run inference through the main binary.
./llama-cli --hf-repo m1guelperez/Medical-Llama3-8B-Q8_0-GGUF --hf-file medical-llama3-8b-q8_0.gguf -p "The meaning to life and the universe is"
or
./llama-server --hf-repo m1guelperez/Medical-Llama3-8B-Q8_0-GGUF --hf-file medical-llama3-8b-q8_0.gguf -c 2048