Instructions to use realitisoft/ai-bot-test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use realitisoft/ai-bot-test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="realitisoft/ai-bot-test")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("realitisoft/ai-bot-test") model = AutoModelForSpeechSeq2Seq.from_pretrained("realitisoft/ai-bot-test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download venv/lib/python3.11/site-packages/prompt_toolkit/formatted_text/pygments.py from realitisoft/ai-bot-test: direct link, hf CLI and curl.
- Browser
- Download file 780 Bytes
-
https://huggingface.co/realitisoft/ai-bot-test/resolve/main/venv/lib/python3.11/site-packages/prompt_toolkit/formatted_text/pygments.py
- Command line
-
hf download hf://realitisoft/ai-bot-test/venv/lib/python3.11/site-packages/prompt_toolkit/formatted_text/pygments.py
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curl -L -o pygments.py https://huggingface.co/realitisoft/ai-bot-test/resolve/main/venv/lib/python3.11/site-packages/prompt_toolkit/formatted_text/pygments.py
780 Bytes
| from __future__ import annotations | |
| from typing import TYPE_CHECKING | |
| from prompt_toolkit.styles.pygments import pygments_token_to_classname | |
| from .base import StyleAndTextTuples | |
| if TYPE_CHECKING: | |
| from pygments.token import Token | |
| __all__ = [ | |
| "PygmentsTokens", | |
| ] | |
| class PygmentsTokens: | |
| """ | |
| Turn a pygments token list into a list of prompt_toolkit text fragments | |
| (``(style_str, text)`` tuples). | |
| """ | |
| def __init__(self, token_list: list[tuple[Token, str]]) -> None: | |
| self.token_list = token_list | |
| def __pt_formatted_text__(self) -> StyleAndTextTuples: | |
| result: StyleAndTextTuples = [] | |
| for token, text in self.token_list: | |
| result.append(("class:" + pygments_token_to_classname(token), text)) | |
| return result | |