Llama-3-11.5B
This model is a Proof of Concept. First 2 Llama-3-8B models has been merged using Mergekit and pre-training continued using QLora and Unsloth for 1000 samples from roneneldan/TinyStories.
Loss still decreases each epoch so I believe this is a successful experiment where there is a lot of room to experiment.
Llama-3-11.5B is a merge of the following models using LazyMergekit:
🧩 Configuration
slices:
- sources:
- model: meta-llama/Meta-Llama-3-8B
layer_range: [0, 24]
- sources:
- model: meta-llama/Meta-Llama-3-8B
layer_range: [8, 32]
merge_method: passthrough
dtype: bfloat16
💻 Usage
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "beratcmn/Llama-3-11.5B"
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"])
Uploaded model
- Developed by: beratcmn
- License: apache-2.0
- Finetuned from model : beratcmn/Llama-3-11.5B
This llama model was trained 2x faster with Unsloth and Huggingface's TRL library.