This model was trained using H2O LLM Studio. — Base model: openlm-research/openllama3b — Dataset preparation: OpenAssistant/oasst1 personalized To use the model with the transformers library on a machine with GPUs, first make sure you have the transformers, accelerate and torch libraries installed. You can print a sample prompt after the preprocessing step to see how it is feed to the tokenizer: Alternatively, you can download h2oaipipeline.py, store it alongside your notebook, and construct the pipeline yourself from the loaded model and tokenizer. If the model and the tokenizer are fully supported in the transformers package, this will allow you to set trustremotecode=False`. You may also construct the pipeline from the loaded model and tokenizer yourself and consider the preprocessing steps: This model was trained using H2O LLM Studio and with the configuration in cfg.yaml. Visit H2O LLM Studio to learn how to train your own large language models. Please read this disclaimer carefully before using the large language model provided in this repository. Your use of the model signifies your agreement to the following terms and conditions. — Biases and Offensiveness: The large…
Модальности:
Генерация текста
Задача: Генерация текста
Автор: h2oai
Теги: llama, gpt, llm, large language model, h2o-llmstudio, en, text-generation-inference
Лайков: 3 | Загрузок: 80
Описание основано на материалах HuggingFace. Перевод выполнен автоматически.
