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AI モデル 85003

• whisper-tiny↗

  Xenova

  https://huggingface.co/openai/whisper-tiny with ONNX weights to be compatible with Transformers.js. If you haven't already, you can install the Transformers.js JavaScript library from NPM using: Note: Having a separate repo for ONNX weights is intended to be a temporary solution until WebML gains more traction. If you would like to make your models web-ready, we recommend converting to ONNX using 🤗 Optimum and structuring your repo like this one (with ONNX weights located in a subfolder named `onnx`).

• accent-classifier↗

  ylacombe

• EAGLE-LLaMA3-Instruct-8B↗

  yuhuili

  EAGLE (Extrapolation Algorithm for Greater Language-model Efficiency) is a new baseline for fast decoding of Large Language Models (LLMs) with provable performance maintenance. This approach involves extrapolating the second-top-layer contextual feature vectors of LLMs, enabling a significant boost in generation efficiency. EAGLE-2 uses the confidence scores from the draft model to approximate acceptance rates, dynamically adjusting the draft tree structure, which further enhances performance. EAGLE-3 removes the feature prediction constraint in EAGLE and simulates this process during training using training-time testing. Considering that top-layer features are limited to next-token prediction, EAGLE-3 replaces them with a fusion of low-, mid-, and high-level semantic features. EAGLE-3 further improves generation speed while ensuring lossless performance.

• d_m12↗

  yuki0011

• bolt-instruct-v2↗

  aisquared

• BAR-2x7B-Math↗

  allenai

• Lumina-Image-2.0↗

  Alpha-VLLM

• rorshark-vit-base↗

  amunchet

  This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the imagefolder dataset. It achieves the following results on the evaluation set: - Loss: 0.0393 - Accuracy: 0.9923 The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 1337 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 5.0 - Transformers 4.36.0.dev0 - Pytorch 2.1.1+cu118 - Datasets 2.15.0 - Tokenizers 0.15.0

• Llama3-1B-Base↗

  andrijdavid

• PULI-LlumiX-32K-instruct-GGUF↗

  ariel-ml