OLMo 7B Twin-2T
OLMo 7B Twin-2T is a released classification and json / tool use model with open-source; evaluate it while provider pricing coverage matures.
Use it for
- Teams evaluating classification and json / tool use
Do not use it for
- Cost-sensitive launches that need sourced token pricing
- Vision or document-understanding workloads
- Family
- OLMo
- Released
- 2024-02-01
- Parameters
- 7B
- Architecture
- Decoder Only
- Knowledge cutoff
- 2023-03
- Specialization
- general
- Openness
- Open source
- License
- Apache 2.0OSI-approvedCommercial use: permitted
- Weights
- Unknown
- Code
- Unknown
- Training
- Fine-tuned
No tracked provider token pricing is available yet.
About
The OLMo 7B Twin-2T is a robust open-source large language model that implements a decoder-only transformer architecture with enhancements for greater stability and performance. It features non-parametric layer normalization and SwiGLU activation functions, along with Rotary positional embeddings for better sequence handling. The model, comprising 32 layers and 32 attention heads, was trained on approximately 2 trillion tokens and supports a context length of 2048. It is notable for its transparency in AI research, as all training data, code, and evaluations are publicly accessible, promoting collaborative advancements.
Top use-case fit
Classification
Included by capability and metadata signals in the decision map.
JSON / Tool use
Included by capability and metadata signals in the decision map.
Provider price ladder
No tracked provider token pricing is available for this model yet.
Available via routers & gateways(1)
Capabilities
Benchmark peer barsfor Classification
No task-mapped benchmark peers are available for this model yet.
Migration checks
No linked migration route is available for this model yet.
No tracked provider token pricing is available yet.