
Yi 34B

Yi 34B is a large language model developed by 01-Ai, a company, featuring 34 billion parameters. It is released under the Apache License 2.0, Yi Series Models Community License Agreement (YSMCLA), and Yi Series Models License Agreement (YSMLA). The model is designed as a bilingual English-Chinese system trained on 3 trillion tokens.
Description of Yi 34B
Yi series models are next-generation open-source large language models trained from scratch by 01.AI. They are bilingual English-Chinese models designed on a 3T multilingual corpus, achieving top-tier performance globally. These models excel in language understanding, commonsense reasoning, and reading comprehension. The Yi-34B-Chat model ranks second after GPT-4 Turbo on the AlpacaEval Leaderboard, while the Yi-34B model leads in both English and Chinese benchmarks.
Parameters & Context Length of Yi 34B
Yi 34B is a large language model with 34 billion parameters and a 200,000-token context length, positioning it in the category of powerful yet resource-intensive systems. The 34b parameter size enables advanced capabilities for complex tasks like multilingual understanding and reasoning, while the 200k context length allows handling extensive texts, though both require significant computational resources. This combination makes Yi 34B suitable for demanding applications where depth and scale are critical.
- Parameter Size: 34b
- Context Length: 200k
Possible Intended Uses of Yi 34B
Yi 34B is a large language model with 34b parameters and support for English and Chinese, offering possible applications in coding, math, and reasoning tasks. Its bilingual capabilities suggest possible utility in multilingual environments, though further exploration is needed to confirm effectiveness. Possible uses could include generating code snippets, solving mathematical problems, or analyzing complex logical scenarios, but these remain possible scenarios requiring thorough testing. The model’s design emphasizes flexibility, making it a candidate for possible experimentation in domains where language and reasoning are critical.
- Intended Uses: coding, math, reasoning
- Supported Languages: english, chinese
- Is_Mono_Lingual: yes
Possible Applications of Yi 34B
Yi 34B is a large language model with 34b parameters and support for English and Chinese, offering possible applications in areas such as possible code generation, possible mathematical problem-solving, possible logical reasoning tasks, and possible multilingual content creation. These possible uses could enhance productivity in technical fields, but each possible application requires thorough evaluation to ensure alignment with specific needs. The model’s bilingual capabilities and reasoning strength suggest possible value in scenarios where language and analytical skills are critical, though further testing is essential.
- Possible Applications: coding, math, reasoning, multilingual content creation
Quantized Versions & Hardware Requirements of Yi 34B
Yi 34B with the q4 quantization offers a possible balance between precision and performance, requiring hardware suitable for models up to 32B parameters, such as multiple GPUs with at least 48GB VRAM total. This setup ensures efficient execution while maintaining reasonable accuracy. Possible users should verify their system’s VRAM and cooling capabilities to support the model’s demands.
- fp16, q2, q3, q4, q5, q6, q8
Conclusion
Yi 34B is a large language model with 34 billion parameters and a 200,000-token context length, designed for bilingual English-Chinese tasks and open-source use. It demonstrates strong performance in coding, math, and reasoning, though potential applications require thorough evaluation before deployment.
References
Benchmarks
Benchmark Name | Score |
---|---|
Instruction Following Evaluation (IFEval) | 30.46 |
Big Bench Hard (BBH) | 35.54 |
Mathematical Reasoning Test (MATH Lvl 5) | 5.14 |
General Purpose Question Answering (GPQA) | 15.55 |
Multimodal Understanding and Reasoning (MUSR) | 9.65 |
Massive Multitask Language Understanding (MMLU-PRO) | 37.91 |
