Llama-3-OpenBioMed-13B-dare-ties
Llama-3-OpenBioMed-13B-dare-ties is a merge of the following models using LazyMergekit:
- aaditya/Llama3-OpenBioLLM-8B
- johnsnowlabs/JSL-MedLlama-3-8B-v1.0
- winninghealth/WiNGPT2-Llama-3-8B-Base
𧩠Configuration
models:
- model: meta-llama/Meta-Llama-3-8B-Instruct
# No parameters necessary for base model
- model: aaditya/Llama3-OpenBioLLM-8B
parameters:
density: 0.53
weight: 0.5
- model: johnsnowlabs/JSL-MedLlama-3-8B-v1.0
parameters:
density: 0.53
weight: 0.3
- model: winninghealth/WiNGPT2-Llama-3-8B-Base
parameters:
density: 0.53
weight: 0.2
merge_method: dare_ties
base_model: meta-llama/Meta-Llama-3-8B-Instruct
parameters:
int8_mask: true
dtype: bfloat16
π» Usage
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "abhinand/Llama-3-OpenBioMed-13B-dare-ties"
messages = [{"role": "user", "content": "What is a large language model?"}]
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"])
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