Instructions to use moetezsa/llama3_charttotext with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use moetezsa/llama3_charttotext with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/llama-3-8b-bnb-4bit") model = PeftModel.from_pretrained(base_model, "moetezsa/llama3_charttotext") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Unsloth Studio
How to use moetezsa/llama3_charttotext 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 moetezsa/llama3_charttotext 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 moetezsa/llama3_charttotext to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for moetezsa/llama3_charttotext to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="moetezsa/llama3_charttotext", max_seq_length=2048, )
- Xet hash:
- da4bcfb4685cde4306e357dbfd44def6100efee050060f8cd14d6e8e804fcacc
- Size of remote file:
- 4.92 kB
- SHA256:
- 15f65bf3b5126b8b1806a933a9bf10e6ba5da5e62963350fefe6f8ecaca38a49
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