BLOOMZ 1.7B
BLOOMZ 1.7B 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 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
- 1.7B
- Architecture
- Decoder Only
- Knowledge cutoff
- 2021
- Specialization
- general
- Training
- finetuned
No tracked provider token pricing is available yet.
About
BLOOMZ 1.7B is a multilingual large language model designed for zero-shot learning, enabling it to follow instructions in various languages without prior training 147. As part of the BLOOMZ and mT0 family, it builds upon the BLOOM and mT5 models. Featuring a decoder-only transformer architecture, it was fine-tuned on the xP3 dataset, which includes diverse tasks and languages 147. While effective in translation, text generation, and question answering, its performance heavily relies on clear prompts and sufficient context 6. However, it is unsuitable for high-stakes applications due to the potential for generating inaccurate information and inherent biases in its training data 3.
BLOOMZ 1.7B is a model in the BLOOMZ family. The structured metadata tracks a 2k-token context window. No headline benchmark score is tracked for BLOOMZ 1.7B 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.