0. TL;DR 1. Model Details 2. Training Details 3. Usage 4. Evaluation 5. Citation — Developed by: https://www.tii.ae — Model type: Causal decoder-only — Architecture: Hybrid Transformers + Mamba architecture — Language(s) (NLP): English, Multilingual — License: Falcon-LLM License For more details about the training protocol of this model, please refer to the Falcon-H1 technical blogpost. Currently to use this model you can either rely on Hugging Face transformers, vLLM or our custom fork of llama.cpp library. Make sure to install the latest version of transformers or vllm, eventually install these packages from source: Refer to the official vLLM documentation for more details on building vLLM from source. Refer to the snippet below to run H1 models using 🤗 transformers: For vLLM, simply start a server by executing the command below: While we are working on integrating our architecture directly into llama.cpp library, you can install our fork of the library and use it directly: https://github.com/tiiuae/llama.cpp-Falcon-H1 Use the same installing guidelines as llama.cpp. Falcon-H1 series perform very well on a variety of tasks, including reasoning tasks. You can check more in detail…
Модальности:
Генерация текста
Области применения:
Диалог / чат Следование инструкциям
Задача: Генерация текста
Автор: tiiuae
Теги: falcon_h1, falcon-h1, conversational, endpoints_compatible, 8-bit, gptq
Лайков: 4 | Загрузок: 90
Описание основано на материалах HuggingFace. Перевод выполнен автоматически.
