Audio-Text-to-Text
Transformers
Safetensors
Chinese
English
edgeinstant
feature-extraction
audio
speech-recognition
speech-translation
audio-question-answering
custom_code
Instructions to use chenjz24/EdgeIn-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use chenjz24/EdgeIn-v1 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("chenjz24/EdgeIn-v1", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 431 Bytes
f74eb65 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | from __future__ import annotations
from dataclasses import dataclass
from enum import Enum
import torch
class AdvanceStatus(str, Enum):
WAIT_INPUT = "WAIT_INPUT"
PRODUCED = "PRODUCED"
END_AUDIO = "END_AUDIO"
FORCED_STOP = "FORCED_STOP"
@dataclass
class GenerationResult:
frames: list[torch.Tensor]
status: AdvanceStatus
actions: list[int]
consumed_text_tokens: int
text_end_consumed: bool
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