genmo/mochi-1-preview
Text-to-Video
•
Updated
•
36k
•
1.12k
Oscar PRO
Skataka
AI & ML interests
None yet
Recent Activity
new activity
about 1 month ago
apple/mistral-coreml:Unable to run the model with SwiftChat sample app
Organizations
None yet
Skataka's activity
Unable to run the model with SwiftChat sample app
1
#10 opened about 1 month ago
by
jfcmelo
liked
a
model
2 months ago
replied to
their
post
3 months ago
Sure, here you go; this data is using my Mac. I haven't been able to test it on an iPhone, as I don't have the 16, but I believe it should also work with the iPhone 16.
Context and Setup
Device used: Mac Studio M1 Ultra 64GB with macOS 15.0.1
Models tested: Mistral7B-Instruct V0.3:
- INT4
- FP16
- Decoding algorithm: Greedy
First Run (Model Adaptation):
This is the initial execution when the app is first launched, and Core ML adapts the model to your device’s hardware. This adaptation process is time-consuming as Core ML optimizes the model to leverage the device’s capabilities in future runs.
| Configuration | Execution Type | Time for First Token (s) | Generation Speed (tokens/s) |
|---|---|---|---|
| INT4 | First Run (Model Adaptation) | 32.81 | - |
| INT4 | Subsequent Runs - First Token | 2.62 | 4.55 |
| INT4 | Additional Iteration | 0.32 | 3.90 |
| FP16 | First Run (Model Adaptation) | 87.28 | - |
| FP16 | Subsequent Runs - First Token | 23.17 | 5.93 |
| FP16 | Additional Iteration | 7.52 | 4.09 |
posted
an
update
3 months ago
Post
2431
SwiftMistralCoreML
Hi Everyone,
I have created a Swift library to interact with Mistral 7B models in CoreML on macOS.
I hope you find it helpful.
https://github.com/cardona/SwiftMistralCoreML
An open-source Swift library that enables macOS and iOS projects to utilize the Mistral-Interact7B models (INT4 and upcoming FP16) in chat mode. This library includes a complete Swift implementation of the tokenizer and Byte Pair Encoding (BPE) encoder, providing an out-of-the-box solution for integrating advanced language models into your Swift applications.
Features
Full Swift Implementation: Includes tokenizer and BPE encoder written entirely in Swift.
CoreML Integration: Leverages Apple's CoreML framework to run Mistral-Interact7B models efficiently.
Multiple Decoding Strategies: Supports Greedy and Top-K sampling, with plans to add more strategies.
Chat Functionality: Designed to work in chat mode for interactive applications.
FP16 Support (Coming Soon): Future version will support FP16 models for improved performance.
Hi Everyone,
I have created a Swift library to interact with Mistral 7B models in CoreML on macOS.
I hope you find it helpful.
https://github.com/cardona/SwiftMistralCoreML
An open-source Swift library that enables macOS and iOS projects to utilize the Mistral-Interact7B models (INT4 and upcoming FP16) in chat mode. This library includes a complete Swift implementation of the tokenizer and Byte Pair Encoding (BPE) encoder, providing an out-of-the-box solution for integrating advanced language models into your Swift applications.
Features
Full Swift Implementation: Includes tokenizer and BPE encoder written entirely in Swift.
CoreML Integration: Leverages Apple's CoreML framework to run Mistral-Interact7B models efficiently.
Multiple Decoding Strategies: Supports Greedy and Top-K sampling, with plans to add more strategies.
Chat Functionality: Designed to work in chat mode for interactive applications.
FP16 Support (Coming Soon): Future version will support FP16 models for improved performance.
-
- 3 replies
liked
a
dataset
over 1 year ago