Text Generation
PEFT
Safetensors
English
lora
llama-3.1
tool-use
embedded-ai
esp32
constitutional-ai
wireclaw-agent
conversational
Instructions to use WhitneyDesignLabs/wireclaw-agent-v1.3.1-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use WhitneyDesignLabs/wireclaw-agent-v1.3.1-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-3.1-8B-Instruct") model = PeftModel.from_pretrained(base_model, "WhitneyDesignLabs/wireclaw-agent-v1.3.1-lora") - Notebooks
- Google Colab
- Kaggle
| [ | |
| { | |
| "epoch": 1.0, | |
| "global_step": 240, | |
| "loss": 0.042953455448150636, | |
| "eval_loss": null, | |
| "learning_rate": 0.00015597732021679152, | |
| "samples_seen": 1920 | |
| }, | |
| { | |
| "epoch": 2.0, | |
| "global_step": 480, | |
| "loss": 0.032810693979263304, | |
| "eval_loss": null, | |
| "learning_rate": 5.3282611893241665e-05, | |
| "samples_seen": 3840 | |
| }, | |
| { | |
| "epoch": 3.0, | |
| "global_step": 720, | |
| "loss": 0.018705502152442932, | |
| "eval_loss": null, | |
| "learning_rate": 1.0128804094233779e-09, | |
| "samples_seen": 5760 | |
| } | |
| ] |