MT0 XL
MT0 XL 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 1k 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
- MT0
- Released
- 2024-01-01
- Context
- 1k
- Parameters
- 3.7B
- Architecture
- Decoder Only
- Specialization
- general
- Training
- finetuned
No tracked provider token pricing is available yet.
About
The MT0 XL is a multilingual large language model with 3.7 billion parameters, developed by the BigScience workshop. It is part of the BLOOMZ and mT0 model families and is designed to execute diverse tasks across various languages through zero-shot capability, achieved via multitask finetuning. This process involves training pre-existing multilingual models, BLOOM and mT5, on a wide range of cross-lingual tasks (xP3). The MT0 XL operates on an architecture similar to the mT5-xl model and has been fine-tuned over 10,000 steps using 1.85 billion tokens on TPUv4-128 hardware. It effectively handles tasks such as translation, question answering, and text generation, among others, making it suitable for applications requiring high linguistic versatility across different languages.
MT0 XL is a model in the MT0 family. The structured metadata tracks a 1k-token context window. No headline benchmark score is tracked for MT0 XL 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.