SeaLLM 7B
SeaLLM 7B has model metadata, but missing tracked provider pricing keeps it from being a default production pick.
Use it for
- Teams evaluating general LLM work
- Workloads that can use a 32k context window
Do not use it for
- Cost-sensitive launches that need sourced token pricing
- Vision or document-understanding workloads
- Strict JSON or tool-calling flows
- Family
- SeaLLM
- Released
- 2024-03-15
- Context
- 32k
- Parameters
- 7B
- Architecture
- Decoder Only
- Specialization
- general
- Training
- finetuned
About
SeaLLM 7B is a multilingual large language model family specifically developed for Southeast Asian languages. Known for its strong multilingual task performance, it often surpasses larger models like GPT-3.5 in specific benchmarks. The models employ a transformer architecture and have undergone various training and fine-tuning processes, including using different base models like Mistral-7B, gemma-7b, and Llama-2. They excel in areas such as math reasoning, instruction following, and function calling while addressing cultural nuances of SEA languages. Despite its capabilities, the model's performance can be subject to the quality and bias of its training data, and it may occasionally produce inaccurate information.
SeaLLM 7B is a model in the SeaLLM family. The structured metadata tracks a 32k-token context window. No headline benchmark score is tracked for SeaLLM 7B yet.
Top use-case fit
No primary decision-task fit is mapped for this model yet.
Provider price ladder
No tracked provider token pricing is available for this model yet.
Capabilities
No model capability flags are currently sourced.
Benchmark peer barsfor Coding
No task-mapped benchmark peers are available for this model yet.
Migration checks
No linked migration route is available for this model yet.