Instructions to use tsystems/colqwen2-7b-v1.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use tsystems/colqwen2-7b-v1.0 with PEFT:
from peft import PeftModel from transformers import AutoModel base_model = AutoModel.from_pretrained("Qwen/Qwen2-VL-7B-Instruct") model = PeftModel.from_pretrained(base_model, "tsystems/colqwen2-7b-v1.0") - Notebooks
- Google Colab
- Kaggle
Download chat_template.json from tsystems/colqwen2-7b-v1.0: direct link, hf CLI and curl.
- Browser
- Download file 1.05 kB
-
https://huggingface.co/tsystems/colqwen2-7b-v1.0/resolve/main/chat_template.json
- Command line
-
hf download hf://tsystems/colqwen2-7b-v1.0/chat_template.json
-
curl -L -o chat_template.json https://huggingface.co/tsystems/colqwen2-7b-v1.0/resolve/main/chat_template.json
1.05 kB
| { | |
| "chat_template": "{% set image_count = namespace(value=0) %}{% set video_count = namespace(value=0) %}{% for message in messages %}{% if loop.first and message['role'] != 'system' %}<|im_start|>system\nYou are a helpful assistant.<|im_end|>\n{% endif %}<|im_start|>{{ message['role'] }}\n{% if message['content'] is string %}{{ message['content'] }}<|im_end|>\n{% else %}{% for content in message['content'] %}{% if content['type'] == 'image' or 'image' in content or 'image_url' in content %}{% set image_count.value = image_count.value + 1 %}{% if add_vision_id %}Picture {{ image_count.value }}: {% endif %}<|vision_start|><|image_pad|><|vision_end|>{% elif content['type'] == 'video' or 'video' in content %}{% set video_count.value = video_count.value + 1 %}{% if add_vision_id %}Video {{ video_count.value }}: {% endif %}<|vision_start|><|video_pad|><|vision_end|>{% elif 'text' in content %}{{ content['text'] }}{% endif %}{% endfor %}<|im_end|>\n{% endif %}{% endfor %}{% if add_generation_prompt %}<|im_start|>assistant\n{% endif %}" | |
| } | |