| | --- |
| | base_model: |
| | - NousResearch/Hermes-3-Llama-3.1-8B |
| | - cognitivecomputations/Dolphin3.0-Llama3.1-8B |
| | tags: |
| | - merge |
| | - mergekit |
| | - lazymergekit |
| | - NousResearch/Hermes-3-Llama-3.1-8B |
| | - cognitivecomputations/Dolphin3.0-Llama3.1-8B |
| | --- |
| | |
| | # NitroOxziT-8B |
| |
|
| | NitroOxziT-8B is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing): |
| | * [NousResearch/Hermes-3-Llama-3.1-8B](https://huggingface.co/NousResearch/Hermes-3-Llama-3.1-8B) |
| | * [cognitivecomputations/Dolphin3.0-Llama3.1-8B](https://huggingface.co/cognitivecomputations/Dolphin3.0-Llama3.1-8B) |
| |
|
| | Don't ask why the weird name, I wanted a modern merge of Hermes and Dolphin so I did it |
| |
|
| | GGUF: [DoesntKnowAI/NitroOxziT-8B-Q8_0-GGUF](https://huggingface.co/DoesntKnowAI/NitroOxziT-8B-Q8_0-GGUF) |
| | ## 🧩 Configuration |
| |
|
| | ```yaml |
| | slices: |
| | - sources: |
| | - model: NousResearch/Hermes-3-Llama-3.1-8B |
| | layer_range: [0, 32] |
| | weight: 0.60 |
| | - model: cognitivecomputations/Dolphin3.0-Llama3.1-8B |
| | layer_range: [0, 32] |
| | weight: 0.40 |
| | merge_method: slerp |
| | parameters: |
| | t: |
| | - model: NousResearch/Hermes-3-Llama-3.1-8B |
| | value: 1.0 |
| | - model: cognitivecomputations/Dolphin3.0-Llama3.1-8B |
| | value: 1.0 |
| | base_model: NousResearch/Hermes-3-Llama-3.1-8B |
| | dtype: bfloat16 |
| | ``` |
| |
|
| | ## 💻 Usage |
| |
|
| | ```python |
| | !pip install -qU transformers accelerate |
| | |
| | from transformers import AutoTokenizer |
| | import transformers |
| | import torch |
| | |
| | model = "DoesntKnowAI/NitroOxziT-8B" |
| | 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"]) |
| | ``` |