WizardCoder Python 7B
WizardCoder Python 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 100k 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
- WizardCoder
- Released
- 2024-01-29
- Context
- 100k
- Parameters
- 7B
- Architecture
- Decoder Only
- Specialization
- general
- Training
- finetuned
No tracked provider token pricing is available yet.
About
The WizardCoder Python 7B model is an advanced large language model by WizardLM, featuring 7 billion parameters and leveraging a sophisticated transformer architecture. It excels in programming-related tasks such as code generation, translation, explanation, and automated debugging. Built on the Llama architecture, the model supports a sequence length of 4096 tokens and operates in the GGUF format, enhancing its adaptability to different input types. Trained on the Evol Instruct Code dataset, it is adept at handling a variety of coding scenarios. However, it may struggle with common sense reasoning and domain-specific knowledge, and its performance varies with the quantization method used. Overall, it is a valuable tool for developers, despite these limitations 1 4 7 3 2.
WizardCoder Python 7B is a model in the WizardCoder family. The structured metadata tracks a 100k-token context window. No headline benchmark score is tracked for WizardCoder Python 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.