migueldeicaza/TensorFlowSharp
TensorFlow API for .NET languages observed · 2026-08-28
Health v2 · maintenance only
10/100
- Activity 0
- Release rhythm 35
- Longevity 100
Flags: no_releases archived
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 3516
- days_rel: n/a
- days_push: 964
- n_releases_24m: 0
Adoption not part of the score
3147 stars · 562 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
TensorFlowSharp provides .NET bindings to the TensorFlow C API, exposing a strongly-typed low-level API for C# and F#. It is designed mainly for running pre-trained TensorFlow models in .NET and is no longer actively maintained in favor of TensorFlow.NET.
Use cases
- run a trained tensorflow model from c#
- load a saved tensorflow graph in a .net application
- use tensorflow from f#
- execute inference with tensorflow on mono or xamarin
- prototype in python keras then run the model in .net
When to choose
- you need to run existing TensorFlow models from C# or F# with a low-level graph/session API
- you are on a legacy .NET/Mono/Xamarin stack and cannot migrate
When to avoid
- you want high-level training APIs or active maintenance - use TensorFlow.NET instead
- you are starting a new machine-learning project in .NET
Facets
library · maturity maintenance
machine-learning deep-learning machine-learning deep-learning dotnet windows cross-platform tensorflow bindings nuget mono xamarin deprecated f-sharp linux macos
1 source
- readme: https://github.com/migueldeicaza/TensorFlowSharp · fetched 2026-08-28 · 34d7b76ce048
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| migueldeicaza/TensorFlowSharp | main | 10 |
For agents
markdown · JSON · MCP: product_card(name="migueldeicaza/TensorFlowSharp")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem