Instructions to use 4yo1/llama_pre2_task08 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use 4yo1/llama_pre2_task08 with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "translation" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("translation", model="4yo1/llama_pre2_task08")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("4yo1/llama_pre2_task08") model = AutoModelForCausalLM.from_pretrained("4yo1/llama_pre2_task08") - Notebooks
- Google Colab
- Kaggle
Model Card for Model ID
Model Details
Model Card: 4yo1/llama_pre2_task08 with Fine-Tuning Model Overview Model Name: 4yo1/llama_pre2_task08
Model Type: Transformer-based Language Model
Model Size: 8 billion parameters
by: 4yo1
Languages: English and Korean
how to use - sample code
from transformers import AutoConfig, AutoModel, AutoTokenizer
config = AutoConfig.from_pretrained("4yo1/llama_pre2_task08")
model = AutoModel.from_pretrained("4yo1/llama_pre2_task08")
tokenizer = AutoTokenizer.from_pretrained("4yo1/llama_pre2_task08")
datasets:
- 140kgpt
license: mit
- Downloads last month
- 7