--- language: - en license: apache-2.0 tags: - merge - mergekit - lazymergekit - meta-llama/Meta-Llama-3-8B - beratcmn/Llama-3-11.5B - text-generation-inference - transformers - unsloth - llama - trl base_model: beratcmn/Llama-3-11.5B --- # 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. [Wandb Report](https://wandb.ai/beratcmn/huggingface/reports/beratcmn-Llama-3-11-5B-v0-1--Vmlldzo3NjUzMTgx) Llama-3-11.5B is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing): * [meta-llama/Meta-Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B) * [meta-llama/Meta-Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B) ## 🧩 Configuration ```yaml 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 ```python !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](https://github.com/unslothai/unsloth) and Huggingface's TRL library. [](https://github.com/unslothai/unsloth)