Image Classification
Transformers
Safetensors
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vision
reward-model
reinforcement-learning
multimodal
llama-factory
Instructions to use OpenDILabCommunity/HUMOR-RM-Keye-VL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenDILabCommunity/HUMOR-RM-Keye-VL with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="OpenDILabCommunity/HUMOR-RM-Keye-VL") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("OpenDILabCommunity/HUMOR-RM-Keye-VL", dtype="auto") - Notebooks
- Google Colab
- Kaggle
File size: 424 Bytes
03e60fb | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | # ollama modelfile auto-generated by llamafactory
FROM .
TEMPLATE """{{ if .System }}<|im_start|>system
{{ .System }}<|im_end|>
{{ end }}{{ range .Messages }}{{ if eq .Role "user" }}<|im_start|>user
{{ .Content }}<|im_end|>
<|im_start|>assistant
{{ else if eq .Role "assistant" }}{{ .Content }}<|im_end|>
{{ end }}{{ end }}"""
SYSTEM """You are a helpful assistant."""
PARAMETER stop "<|im_end|>"
PARAMETER num_ctx 4096
|