","eos_token":"<|end_of_text|>"}},"createdAt":"2024-05-01T07:53:45.000Z","discussionsDisabled":false,"downloads":1359,"downloadsAllTime":1359,"id":"rinna/llama-3-youko-8b","isLikedByUser":false,"isWatchedByUser":false,"inference":"ExplicitOptOut","lastModified":"2024-05-07T01:59:47.000Z","likes":28,"pipeline_tag":"text-generation","library_name":"transformers","librariesOther":[],"model-index":nul
This dataset was created by automatically translating "databricks-dolly-15k" into Japanese. This dataset is licensed under CC-BY-SA-3.0 Last Update : 2023-05-11 databricks-dolly-15k-ja https://github.com/kunishou/databricks-dolly-15k-ja databricks-dolly-15k https://github.com/databrickslabs/dolly/tree/master/data
","chat_template":"{% set loop_messages = messages %}{% for message in loop_messages %}{% set content = '<|start_header_id|>' + message['role'] + '<|end_header_id|>\n\n'+ message['content'] | trim + '<|eot_id|>' %}{% if loop.index0 == 0 %}{% set content = bos_token + content %}{% endif %}{{ content }}{% endfor %}{% if add_generation_prompt %}{{ '<|start_header_id|>assistant<|end_header_id|>\n\n' }
Discover amazing ML apps made by the community
Discover amazing ML apps made by the community
Discover amazing ML apps made by the community
Japanese Stable LM Base Gamma 7B Model Description This is a 7B-parameter decoder-only language model with a focus on maximizing Japanese language modeling performance and Japanese downstream task performance. We conducted continued pretraining using Japanese data on the English language model, Mistral-7B-v0.1, to transfer the model's knowledge and capabilities to Japanese. If you are looking for
Please note that both Megatron-LM and DeepSpeed have Pipeline Parallelism and BF16 Optimizer implementations, but we used the ones from DeepSpeed as they are integrated with ZeRO. Megatron-DeepSpeed implements 3D Parallelism to allow huge models to train in a very efficient way. Let’s briefly discuss the 3D components. DataParallel (DP) - the same setup is replicated multiple times, and each being
🤗 コースへようこそ! このコースでは、Hugging Faceのエコシステムを形成するライブラリである🤗 Transformers、🤗 Datasets、🤗 Tokenizers、🤗 Accelerate、そしてHugging Face Hubを使って自然言語処理(NLP)について学習することができます。このコースは、完全に無料で取り組むことができ、広告もありません。 何を学ぶことができるのか? こちらがこのコースの概要になります: 第1章から第4章では、🤗 Transformersライブラリのメインコンセプトを紹介します。このパートを終える頃には、Transformerモデルがどのように機能するかを理解し、Hugging Face Hubにあるモデルを利用し、データセットでfine-tuningを行い、その成果をHub上で共有する方法を身につけることができるでしょう! 第5
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