Feature Extraction
Transformers
Safetensors
English
qwen2_vl
image-text-to-text
multimodal-embedding
universal-multimodal-embedding
retrieval
latent-reasoning
mllm
qwen2-vl
Instructions to use Rem520/PLUME-7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Rem520/PLUME-7B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Rem520/PLUME-7B")# Load model directly from transformers import AutoProcessor, AutoModelForImageTextToText processor = AutoProcessor.from_pretrained("Rem520/PLUME-7B") model = AutoModelForImageTextToText.from_pretrained("Rem520/PLUME-7B") - Notebooks
- Google Colab
- Kaggle
| { | |
| "<bot>": 151659, | |
| "<ct>": 151661, | |
| "<disc_emb>": 151658, | |
| "<eot>": 151660, | |
| "<gen_emb>": 151657, | |
| "<|box_end|>": 151649, | |
| "<|box_start|>": 151648, | |
| "<|endoftext|>": 151643, | |
| "<|im_end|>": 151645, | |
| "<|im_start|>": 151644, | |
| "<|image_pad|>": 151655, | |
| "<|object_ref_end|>": 151647, | |
| "<|object_ref_start|>": 151646, | |
| "<|quad_end|>": 151651, | |
| "<|quad_start|>": 151650, | |
| "<|video_pad|>": 151656, | |
| "<|vision_end|>": 151653, | |
| "<|vision_pad|>": 151654, | |
| "<|vision_start|>": 151652 | |
| } | |