BLOOMZ 3B
BLOOMZ 3B 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 2k 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
- BLOOMZ
- Released
- 2022-07-20
- Context
- 2k
- Parameters
- 3B
- Architecture
- Decoder Only
- Knowledge cutoff
- 2021
- Specialization
- general
- Training
- finetuned
No tracked provider token pricing is available yet.
About
BLOOMZ 3B is a multilingual large language model created by the BigScience workshop. It leverages around 3 billion parameters and a Transformer architecture, enabling it to perform diverse tasks like translation, summarization, and question answering in several languages. Its fine-tuning on the xP3 dataset allows effective cross-lingual performance, although its efficacy can be influenced by prompt structure. The model’s training required significant computational resources, utilizing 128 A100 GPUs over 2000 finetuning steps. While offering efficient inference and zero-shot capabilities, its functionality may vary with prompt and multilingual tasks without specific adaptations.
BLOOMZ 3B is a model in the BLOOMZ family. The structured metadata tracks a 2k-token context window. No headline benchmark score is tracked for BLOOMZ 3B 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.