Instructions to use fischmacro/Fisch.Macro.Script.Mobile.No.Key.Latest.version with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- fastai
How to use fischmacro/Fisch.Macro.Script.Mobile.No.Key.Latest.version with fastai:
from huggingface_hub import from_pretrained_fastai learn = from_pretrained_fastai("fischmacro/Fisch.Macro.Script.Mobile.No.Key.Latest.version") - Notebooks
- Google Colab
- Kaggle
File size: 962 Bytes
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license: cc-by-2.0
datasets:
- yahma/alpaca-cleaned
language:
- el
- aa
metrics:
- Josh98/nl2bash_m
base_model:
- AIDC-AI/Marco-o1
pipeline_tag: fill-mask
library_name: fastai
tags:
- art
---
💪💪 [New update version Try here](https://play.eslgaming.com/player/myinfos/20511613/)
Feature :
. Auto Farm
. AFK Auto Fish
. inf money
. Fully Auto Missions
. Auto Quest
. Instant Kill
. Bring
. Collect Item
. Open Chest
. Bypass Level
. Instant Level
& More!
The stain normalizer has a native Tensorflow transform and can be directly applied to a tf.data.Dataset:
# Map the stain normalizer transformation
# to a tf.data.Dataset
dataset = dataset.map(normalizer.tf_to_tf)
Alternatively, the model can be used to generate predictions for whole-slide images processed through Slideflow in an end-to-end Project. To use the model to generate predictions on data processed with Slideflow, simply pass the model to the Project.predict() function:
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