--- tags: - merge - mergekit - mistral - Intel/neural-chat-7b-v3-3 - cognitivecomputations/samantha-mistral-7b base_model: - Intel/neural-chat-7b-v3-3 - cognitivecomputations/samantha-mistral-7b --- # SamChat SamChat is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing): * [Intel/neural-chat-7b-v3-3](https://huggingface.co/Intel/neural-chat-7b-v3-3) * [cognitivecomputations/samantha-mistral-7b](https://huggingface.co/cognitivecomputations/samantha-mistral-7b) ## 🧩 Configuration ```yaml models: - model: macadeliccc/WestLake-7B-v2-laser-truthy-dpo # no params for base model - model: Intel/neural-chat-7b-v3-3 parameters: weight: 0.55 density: 0.46 - model: cognitivecomputations/samantha-mistral-7b parameters: weight: 0.64 density: 0.55 merge_method: dare_ties base_model: macadeliccc/WestLake-7B-v2-laser-truthy-dpo parameters: normalize: true int8_mask: true dtype: float16 ``` ## 💻 Usage ```python !pip install -qU transformers accelerate from transformers import AutoTokenizer import transformers import torch model = "fhai50032/SamChat" 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"]) ```