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AWQ quants
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metadata
base_model: meta-llama/Meta-Llama-3-8B
tags:
  - llama-3
  - llama
  - Mixtral
  - instruct
  - finetune
  - chatml
  - DPO
  - RLHF
  - gpt4
  - distillation
model-index:
  - name: OpenBioLLM-8B
    results: []
license: llama3
language:
  - en
widget:
  - example_title: OpenBioLLM-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:

        1. Physiological jaundice: This is the most common type of newborn
        jaundice and usually appears within 24-72 hours after birth. It tends to
        peak between the second and fifth day of life and gradually improves
        over the next week or two. By the time the baby is one week old, the
        jaundice should have mostly resolved. 2. Breast milk jaundice: This type
        of jaundice occurs in breastfed babies and may appear later than
        physiological jaundice, typically between the fifth and fourteenth day
        of life. It tends to persist for a longer duration but usually resolves
        within six weeks after birth. 3. Pathological jaundice: This type of
        jaundice is less common and occurs due to an underlying medical
        condition that affects bilirubin metabolism or liver function. The
        duration of pathological jaundice depends on the specific cause and may
        require treatment.

        It's important for parents to monitor their newborn's jaundice closely
        and seek medical advice if the jaundice progresses rapidly, becomes
        severe, or is accompanied by other symptoms such as poor feeding,
        lethargy, or excessive sleepiness. In these cases, further evaluation
        and management may be necessary. Remember that each baby is unique, and
        the timing of jaundice resolution can vary. If you have concerns about
        your newborn's jaundice, it's always best to consult with a healthcare
        professional for personalized advice and guidance.
quantized_by: bartowski
pipeline_tag: text-generation

4-bit GEMM AWQ Quantizations of OpenBioLLM-Llama3-8B

Using AutoAWQ release v0.2.4 for quantization.

Original model: https://huggingface.co/aaditya/OpenBioLLM-Llama3-8B

Prompt format

No chat template specified so default is used. This may be incorrect, check original model card for details.

<|im_start|>system
{system_prompt}<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
<|im_start|>assistant

AWQ Parameters

  • q_group_size: 128
  • w_bit: 4
  • zero_point: True
  • version: GEMM

How to run

From the AutoAWQ repo here

First install autoawq pypi package:

pip install autoawq

Then run the following:

from awq import AutoAWQForCausalLM
from transformers import AutoTokenizer, TextStreamer


quant_path = "models/OpenBioLLM-Llama3-8B-AWQ"

# Load model
model = AutoAWQForCausalLM.from_quantized(quant_path, fuse_layers=True)
tokenizer = AutoTokenizer.from_pretrained(quant_path, trust_remote_code=True)
streamer = TextStreamer(tokenizer, skip_prompt=True, skip_special_tokens=True)

prompt = "You're standing on the surface of the Earth. "\
        "You walk one mile south, one mile west and one mile north. "\
        "You end up exactly where you started. Where are you?"

chat = [
    {"role": "system", "content": "You are a concise assistant that helps answer questions."},
    {"role": "user", "content": prompt},
]

# <|eot_id|> used for llama 3 models
terminators = [
    tokenizer.eos_token_id,
    tokenizer.convert_tokens_to_ids("<|eot_id|>")
]

tokens = tokenizer.apply_chat_template(
    chat,
    return_tensors="pt"
).cuda()

# Generate output
generation_output = model.generate(
    tokens, 
    streamer=streamer,
    max_new_tokens=64,
    eos_token_id=terminators
)

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