Instructions to use kunal732/timesfm-2.5-200m-transformers-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use kunal732/timesfm-2.5-200m-transformers-mlx with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir timesfm-2.5-200m-transformers-mlx kunal732/timesfm-2.5-200m-transformers-mlx
- TimesFM
How to use kunal732/timesfm-2.5-200m-transformers-mlx with TimesFM:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
kunal732/timesfm-2.5-200m-transformers-mlx
This model was converted from google/timesfm-2.5-200m-transformers
using MLX-Swift-TS.
Use with MLX-Swift-TS
import MLXTimeSeries
let forecaster = try await TimeSeriesForecaster.loadFromHub(id: "kunal732/timesfm-2.5-200m-transformers-mlx")
let input = TimeSeriesInput.univariate(historicalValues)
let prediction = forecaster.forecast(input: input, predictionLength: 64)
Original Model
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Model size
0.2B params
Tensor type
F16
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Base model
google/timesfm-2.5-200m-transformers