Text Generation
PEFT
Safetensors
lora
small-language-model
enterprise-benchmark
code-generation
conversational
Instructions to use yusifnuri/Llama-3.2-3B-Instruct_code_generation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use yusifnuri/Llama-3.2-3B-Instruct_code_generation with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-3.2-3B-Instruct") model = PeftModel.from_pretrained(base_model, "yusifnuri/Llama-3.2-3B-Instruct_code_generation") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from yusifnuri/Llama-3.2-3B-Instruct_code_generation: direct link, hf CLI and curl.
- Browser
- Download file 17.2 MB
-
https://huggingface.co/yusifnuri/Llama-3.2-3B-Instruct_code_generation/resolve/main/tokenizer.json
- Command line
-
hf download hf://yusifnuri/Llama-3.2-3B-Instruct_code_generation/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/yusifnuri/Llama-3.2-3B-Instruct_code_generation/resolve/main/tokenizer.json
17.2 MB
- Xet hash:
- c4530699d0209a307783c8d39f35cd73dc23b5429abaaa6604036ce2b1b2ebf2
- Size of remote file:
- 17.2 MB
- SHA256:
- 9c85066e7642934ed09b44155e6566b0b5dab2637fb9433439ba5c9c7f8b50d3
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