README.md

metadata

tags:
  - merge
  - mergekit
  - lazymergekit
  - aaditya/Llama3-OpenBioLLM-8B
base_model:
  - aaditya/Llama3-OpenBioLLM-8B
license: llama3
language:
  - en

Llama-3-Galen-8B-32k-v1

Llama-3-Galen-8B-32k-v1 is a RoPE scaled, DARE TIES merge of the following models using LazyMergekit:

• aaditya/Llama3-OpenBioLLM-8B
• johnsnowlabs/JSL-MedLlama-3-8B-v2.0

This model is capable of handling a context size of 32K right out of the box, enabled with Dynamic RoPE scaling.

🧩 Configuration

models:
  - model: johnsnowlabs/JSL-MedLlama-3-8B-v2.0
    # No parameters necessary for base model
  - model: aaditya/Llama3-OpenBioLLM-8B
    parameters:
      density: 0.53
      weight: 0.5
merge_method: dare_ties
base_model: johnsnowlabs/JSL-MedLlama-3-8B-v2.0
parameters:
  int8_mask: true
dtype: bfloat16

💻 Usage

!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "abhinand/Llama-3-Galen-8B-32k-v1"
messages = [{"role": "user", "content": "How long does it take to recover from COVID-19?"}]

tokenizer = AutoTokenizer.from_pretrained(model)
prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
pipeline = transformers.pipeline(
    "text-generation",
    model=model,
    torch_dtype=torch.float16,
    device_map="auto",
)

outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
print(outputs[0]["generated_text"])