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 and Technical Report. Currently to use this model you can either rely on Hugging Face transformers, vLLM or our llama.cpp library. Make sure to install the latest version of transformers or vllm, eventually install these packages from source: Refer to the snippet below to run H1 models using 🤗 transformers: For vLLM, simply start a server by executing the command below: You can find all GGUF files compatible with llama.cpp under our official collection Falcon-H1 series perform very well on a variety of tasks, including reasoning tasks. You can check more in detail on our our release blogpost, detailed benchmarks. — View our release blogpost. — View our technical report. — Feel free to join our discord server if you have any questions or to interact with our researchers and developers. If the…
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Автор: tiiuae
Теги: falcon_h1, falcon-h1, ar, cs, de, en, es, fr
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Описание основано на материалах HuggingFace. Перевод выполнен автоматически.
