ruslanmv/ai-medical-chatbot
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How to use kingabzpro/llama-3-8b-chat-doctor with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("question-answering", model="kingabzpro/llama-3-8b-chat-doctor")
messages = [
{"role": "user", "content": "Who are you?"},
]
pipe(messages) # Load model directly
from transformers import AutoTokenizer, AutoModelForMultimodalLM
tokenizer = AutoTokenizer.from_pretrained("kingabzpro/llama-3-8b-chat-doctor")
model = AutoModelForMultimodalLM.from_pretrained("kingabzpro/llama-3-8b-chat-doctor")
messages = [
{"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
messages,
add_generation_prompt=True,
tokenize=True,
return_dict=True,
return_tensors="pt",
).to(model.device)
outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))How to use kingabzpro/llama-3-8b-chat-doctor with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="kingabzpro/llama-3-8b-chat-doctor", filename="llama-3-8b-chat-doctor-Q4_K_M.gguf", )
llm.create_chat_completion(
messages = "{\n \"question\": \"What is my name?\",\n \"context\": \"My name is Clara and I live in Berkeley.\"\n}"
)How to use kingabzpro/llama-3-8b-chat-doctor with llama.cpp:
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf kingabzpro/llama-3-8b-chat-doctor:Q4_K_M # Run inference directly in the terminal: llama-cli -hf kingabzpro/llama-3-8b-chat-doctor:Q4_K_M
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf kingabzpro/llama-3-8b-chat-doctor:Q4_K_M # Run inference directly in the terminal: llama-cli -hf kingabzpro/llama-3-8b-chat-doctor:Q4_K_M
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf kingabzpro/llama-3-8b-chat-doctor:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf kingabzpro/llama-3-8b-chat-doctor:Q4_K_M
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf kingabzpro/llama-3-8b-chat-doctor:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf kingabzpro/llama-3-8b-chat-doctor:Q4_K_M
docker model run hf.co/kingabzpro/llama-3-8b-chat-doctor:Q4_K_M
How to use kingabzpro/llama-3-8b-chat-doctor with Ollama:
ollama run hf.co/kingabzpro/llama-3-8b-chat-doctor:Q4_K_M
How to use kingabzpro/llama-3-8b-chat-doctor with Unsloth Studio:
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for kingabzpro/llama-3-8b-chat-doctor to start chatting
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for kingabzpro/llama-3-8b-chat-doctor to start chatting
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for kingabzpro/llama-3-8b-chat-doctor to start chatting
How to use kingabzpro/llama-3-8b-chat-doctor with Docker Model Runner:
docker model run hf.co/kingabzpro/llama-3-8b-chat-doctor:Q4_K_M
How to use kingabzpro/llama-3-8b-chat-doctor with Lemonade:
# Download Lemonade from https://lemonade-server.ai/ lemonade pull kingabzpro/llama-3-8b-chat-doctor:Q4_K_M
lemonade run user.llama-3-8b-chat-doctor-Q4_K_M
lemonade list
This model is a fine-tuned version of meta-llama/Meta-Llama-3-8B-Instruct on an ruslanmv/ai-medical-chatbot dataset.
It contains the adopter, full model, and quantized GGUF file for using it locally.