InternLM XComposer 7B
InternLM XComposer 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 4k 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
- InternLM-XComposer
- Released
- 2023-10-13
- Context
- 4k
- Parameters
- 7B
- Architecture
- Decoder Only
- Knowledge cutoff
- 2023-03
- Specialization
- general
- Training
- finetuned
About
InternLM-XComposer 7B is a state-of-the-art vision-language large model with a 7 billion parameter architecture, designed for advanced tasks involving text and image integration. It combines a refined version of CLIP as a vision encoder with the InternLM2-based language model, effectively achieving capabilities similar to GPT-4V but with a more compact size. Utilizing techniques like Partial LoRA for enhanced alignment, this model is adept at generating coherent text-image compositions, analyzing images and videos, and even automating webpage creation. Trained on diverse datasets with an extended context capability, it excels in detailed visual comprehension and dynamic multi-turn dialogues, making it ideal for applications in content creation and AI analysis.
InternLM XComposer 7B is a model in the InternLM-XComposer family. The structured metadata tracks a 4k-token context window. No headline benchmark score is tracked for InternLM XComposer 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.