Can you tell me a little bit more about your plans? StableLM: That’s wonderful! It’s great to hear that you’ll be visiting your grandma in Toronto. She’s a person who loves gardens and flowers. StableLM: Hello John! It’s always a pleasure to meet new people. User: Hey! My name is John nice to meet you! StableLM Tuned should be used with prompts formatted to. decode( tokens, skip_special_tokens = True)) Stopping_criteria = StoppingCriteriaList() """ prompt = f" What's your mood today?" inputs = tokenizer( prompt, return_tensors = "pt"). StableLM will refuse to participate in anything that could harm a human. StableLM is more than just an information source, StableLM is also able to write poetry, short stories, and make jokes. StableLM is excited to be able to help the user, but will refuse to do anything that could be considered harmful to the user. Return input_ids in stop_ids system_prompt = """# StableLM Tuned (Alpha version) - StableLM is a helpful and harmless open-source AI language model developed by StabilityAI. from_pretrained( "stabilityai/stablelm-tuned-alpha-7b")ĭef _call_( self, input_ids: torch. from_pretrained( "stabilityai/stablelm-tuned-alpha-7b") Import torch from transformers import AutoModelForCausalLM, AutoTokenizer, StoppingCriteria, StoppingCriteriaList tokenizer = AutoTokenizer. Get started chatting with StableLM-Tuned-Alpha by using the following code snippet: Check out this notebook to run inference with limited GPU capabilities. SizeĪll StableLM models are hosted on the Hugging Face hub. We will be releasing these models as StableLM-Tuned-Alpha. The context length for these models is 4096 tokens.Īn upcoming technical report will document the model specifications and the training settings.Īs a proof-of-concept, we also fine-tuned the model with Stanford Alpaca's procedure using a combination of five recent datasets for conversational agents: Stanford's Alpaca, Nomic-AI's gpt4all, RyokoAI's ShareGPT52K datasets, Databricks labs' Dolly, and Anthropic's HH. These models will be trained on up to 1.5 trillion tokens. StableLM-Alpha models are trained on the new dataset that build on The Pile, which contains 1.5 trillion tokens, roughly 3x the size of The Pile. Please visit HuggingFace checkpoint for more information about how to combine our delta weights with the original model. StableVicuna's delta weights are released under ( CC BY-NC-SA-4.0). Phung leading the training effort.ĭue to the original non-commercial license of LLaMA, we can only release the weights of our model as deltas over the original model's weights. This model is developed by StabilityAI's CarperAI team, with Duy V. It is our attempt at creating an open-source RLHF LLM Chatbot. StableVicuna is an RLHF fine-tune of Vicuna-13B v0, which itself is a fine-tune of LLaMA-13B. Try to chat with our 7B model, StableLM-Tuned-Alpha-7B, on Hugging Face Spaces. Base models are released under CC BY-SA-4.0. Released initial set of StableLM-alpha models, with 3B and 7B parameters. Delta weights over the original Llama model is released under ( CC BY-NC-SA-4.0).
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