--- base_model: - Casual-Autopsy/L3-Umbral-Mind-RP-v1.0-8B - aifeifei798/llama3-8B-DarkIdol-2.1-Uncensored-32K - Nitral-AI/Hathor_Stable-v0.2-L3-8B - Sao10K/L3-8B-Stheno-v3.1 tags: - merge - mergekit - lazymergekit - Casual-Autopsy/L3-Umbral-Mind-RP-v1.0-8B - aifeifei798/llama3-8B-DarkIdol-2.1-Uncensored-32K - Nitral-AI/Hathor_Stable-v0.2-L3-8B - Sao10K/L3-8B-Stheno-v3.1 --- # L3-Umbral-Mind-RP-v2.0-8B L3-Umbral-Mind-RP-v2.0-8B is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing): * [Casual-Autopsy/L3-Umbral-Mind-RP-v1.0-8B](https://huggingface.co/Casual-Autopsy/L3-Umbral-Mind-RP-v1.0-8B) * [aifeifei798/llama3-8B-DarkIdol-2.1-Uncensored-32K](https://huggingface.co/aifeifei798/llama3-8B-DarkIdol-2.1-Uncensored-32K) * [Nitral-AI/Hathor_Stable-v0.2-L3-8B](https://huggingface.co/Nitral-AI/Hathor_Stable-v0.2-L3-8B) * [Sao10K/L3-8B-Stheno-v3.1](https://huggingface.co/Sao10K/L3-8B-Stheno-v3.1) ## 🧩 Configuration ```yaml models: - model: Casual-Autopsy/Umbral-Mind-3 - model: Casual-Autopsy/L3-Umbral-Mind-RP-v1.0-8B parameters: weight: 0.04 - model: aifeifei798/llama3-8B-DarkIdol-2.1-Uncensored-32K parameters: weight: 0.02 - model: Nitral-AI/Hathor_Stable-v0.2-L3-8B parameters: weight: 0.02 - model: Sao10K/L3-8B-Stheno-v3.1 parameters: weight: 0.01 merge_method: task_arithmetic base_model: Casual-Autopsy/Umbral-Mind-3 dtype: bfloat16 ``` ## 💻 Usage ```python !pip install -qU transformers accelerate from transformers import AutoTokenizer import transformers import torch model = "Casual-Autopsy/L3-Umbral-Mind-RP-v2.0-8B" 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"]) ```