Image Segmentation
Transformers
Safetensors
English
falcon_x
feature-extraction
falcon-x
vision-language
custom_code
Instructions to use JonathanJMK/FALCON with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JonathanJMK/FALCON with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="JonathanJMK/FALCON", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("JonathanJMK/FALCON", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 711 Bytes
c645013 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | Llama 2 is licensed under the LLAMA 2 Community License, Copyright (c) Meta
Platforms, Inc. All Rights Reserved.
Vicuna-7B-v1.5: LMSYS, derived from Llama 2.
https://huggingface.co/lmsys/vicuna-7b-v1.5
License: LICENSE-Llama-2. Acceptable Use Policy:
https://huggingface.co/meta-llama/Llama-2-7b/blob/main/USE_POLICY.md
DINOv2: Meta Platforms, Inc. and affiliates, Apache-2.0.
https://github.com/facebookresearch/dinov2
RF-DETR segmentation 1.5.2: Roboflow, Apache-2.0.
https://github.com/roboflow/rf-detr/tree/1.5.2
FALCON code: Apache-2.0. See LICENSE-code for the Apache-2.0 license text.
The final model includes fine-tuned detector, adapter and LoRA weights;
upstream model licenses remain applicable.
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