Llama-3-OpenBioMed-8B-dare-ties-4x
Llama-3-OpenBioMed-8B-dare-ties-4x is a merge of the following models using LazyMergekit:
- aaditya/Llama3-OpenBioLLM-8B
- johnsnowlabs/JSL-MedLlama-3-8B-v2.0
- Jayant9928/orpo_med_v3
- skumar9/Llama-medx_v3
🧩 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: 0.2
- model: johnsnowlabs/JSL-MedLlama-3-8B-v2.0
parameters:
density: 0.53
weight: 0.3
- model: Jayant9928/orpo_med_v3
parameters:
density: 0.53
weight: 0.3
- model: skumar9/Llama-medx_v3
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
💻 Usage
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "abhinand/Llama-3-OpenBioMed-8B-dare-ties-4x"
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"])