Image-Text-to-Text
Transformers
English
Chinese
eviscene
multimodal
image-factuality
agent
sft
distillation
Instructions to use ZiAnwang/EviScene with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ZiAnwang/EviScene with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="ZiAnwang/EviScene")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ZiAnwang/EviScene", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use ZiAnwang/EviScene with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "ZiAnwang/EviScene" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ZiAnwang/EviScene", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/ZiAnwang/EviScene
- SGLang
How to use ZiAnwang/EviScene with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "ZiAnwang/EviScene" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ZiAnwang/EviScene", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "ZiAnwang/EviScene" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ZiAnwang/EviScene", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use ZiAnwang/EviScene with Docker Model Runner:
docker model run hf.co/ZiAnwang/EviScene
Download eviscene/render_trace_html.py from ZiAnwang/EviScene: direct link, hf CLI and curl.
- Browser
- Download file 1.67 kB
-
https://huggingface.co/ZiAnwang/EviScene/resolve/main/eviscene/render_trace_html.py
- Command line
-
hf download hf://ZiAnwang/EviScene/eviscene/render_trace_html.py
-
curl -L -o render_trace_html.py https://huggingface.co/ZiAnwang/EviScene/resolve/main/eviscene/render_trace_html.py
1.67 kB
| # -*- coding: utf-8 -*- | |
| """CLI for rendering one or more trace JSON files into HTML viewers.""" | |
| from __future__ import annotations | |
| import argparse | |
| import os | |
| from typing import Iterable, List | |
| from eviscene.trace_viewer import render_trace_file | |
| def _iter_trace_files(path: str) -> Iterable[str]: | |
| if os.path.isfile(path): | |
| if path.lower().endswith(".json"): | |
| yield path | |
| return | |
| for root, _, files in os.walk(path): | |
| for name in files: | |
| if name.lower().endswith(".json"): | |
| yield os.path.join(root, name) | |
| def main() -> None: | |
| parser = argparse.ArgumentParser(description="Render trace JSON files to standalone HTML viewers") | |
| parser.add_argument("input_path", help="A trace JSON file or a directory containing trace JSON files") | |
| parser.add_argument("--output-dir", default="", help="Optional output directory for generated HTML files") | |
| args = parser.parse_args() | |
| trace_files: List[str] = list(_iter_trace_files(args.input_path)) | |
| if not trace_files: | |
| raise SystemExit(f"No trace JSON files found under: {args.input_path}") | |
| generated = 0 | |
| for json_path in trace_files: | |
| if args.output_dir: | |
| os.makedirs(args.output_dir, exist_ok=True) | |
| html_name = os.path.splitext(os.path.basename(json_path))[0] + ".html" | |
| html_path = os.path.join(args.output_dir, html_name) | |
| else: | |
| html_path = os.path.splitext(json_path)[0] + ".html" | |
| render_trace_file(json_path, html_path) | |
| print(html_path) | |
| generated += 1 | |
| print(f"Rendered {generated} HTML file(s).") | |
| if __name__ == "__main__": | |
| main() | |