Visual Question Answering
Transformers
Safetensors
English
qwen3_vl
image-text-to-text
text-generation-inference
unsloth
8-bit precision
compressed-tensors
Instructions to use Tesleum/0xDental with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Tesleum/0xDental with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("visual-question-answering", model="Tesleum/0xDental")# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("Tesleum/0xDental") model = AutoModelForMultimodalLM.from_pretrained("Tesleum/0xDental", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use Tesleum/0xDental with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for Tesleum/0xDental to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for Tesleum/0xDental to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Tesleum/0xDental to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="Tesleum/0xDental", max_seq_length=2048, )
- Xet hash:
- dde3c5a4d468da6fe61f11ffa8f04af2d101f8f4a0fe118c37bd31bb8c3017b6
- Size of remote file:
- 11.4 MB
- SHA256:
- be75606093db2094d7cd20f3c2f385c212750648bd6ea4fb2bf507a6a4c55506
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