PEFT
TensorBoard
Safetensors
llama
trl
sft
unsloth
Generated from Trainer
4-bit precision
bitsandbytes
Instructions to use stacklok/CodeLlama-7b-hf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use stacklok/CodeLlama-7b-hf with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/codellama-7b-bnb-4bit") model = PeftModel.from_pretrained(base_model, "stacklok/CodeLlama-7b-hf") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use stacklok/CodeLlama-7b-hf 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 stacklok/CodeLlama-7b-hf 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 stacklok/CodeLlama-7b-hf to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for stacklok/CodeLlama-7b-hf to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="stacklok/CodeLlama-7b-hf", max_seq_length=2048, )
| { | |
| "_from_model_config": true, | |
| "bos_token_id": 1, | |
| "eos_token_id": 2, | |
| "max_length": 16384, | |
| "pad_token_id": 0, | |
| "transformers_version": "4.44.2" | |
| } | |