Instructions to use arham6/tmp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use arham6/tmp with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("deepseek-ai/deepseek-llm-7b-chat") model = PeftModel.from_pretrained(base_model, "arham6/tmp") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use arham6/tmp 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 arham6/tmp 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 arham6/tmp to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for arham6/tmp to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="arham6/tmp", max_seq_length=2048, )
- Xet hash:
- 5854d123767206fa3557fc05081c4e04af1f2507ab4eeb6decf0b11cd25d0d56
- Size of remote file:
- 600 MB
- SHA256:
- fe9cb96d5770098154f0e1e98de3e31b1a260844a3270c298c892ea4e50cdac6
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