Video-Text-to-Text
Transformers
Safetensors
MLX
English
qwen2_5_vl
image-text-to-text
video-grounding
temporal-grounding
video-understanding
qwen2-vl
mlx-my-repo
text-generation-inference
4-bit precision
Instructions to use JungleGym/TimeLens-7B-mlx-4Bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JungleGym/TimeLens-7B-mlx-4Bit with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("JungleGym/TimeLens-7B-mlx-4Bit") model = AutoModelForMultimodalLM.from_pretrained("JungleGym/TimeLens-7B-mlx-4Bit", device_map="auto") - MLX
How to use JungleGym/TimeLens-7B-mlx-4Bit with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download JungleGym/TimeLens-7B-mlx-4Bit --local-dir TimeLens-7B-mlx-4Bit
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
Download tokenizer.json from JungleGym/TimeLens-7B-mlx-4Bit: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/JungleGym/TimeLens-7B-mlx-4Bit/resolve/main/tokenizer.json
- Command line
-
hf download hf://JungleGym/TimeLens-7B-mlx-4Bit/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/JungleGym/TimeLens-7B-mlx-4Bit/resolve/main/tokenizer.json
11.4 MB
- Xet hash:
- 4bd2f092eeec244c0448f13e31edd4b25e625568713e4155993a3dea90c7437a
- Size of remote file:
- 11.4 MB
- SHA256:
- 9c5ae00e602b8860cbd784ba82a8aa14e8feecec692e7076590d014d7b7fdafa
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