Text Generation
PEFT
Safetensors
English
lora
qwen2.5-coder
verilog
eda
dft
test-point-insertion
reinforcement-learning
grpo
conversational
Instructions to use SKLP-EDA-LAB/Tesla-Pro-TPI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use SKLP-EDA-LAB/Tesla-Pro-TPI with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2.5-Coder-7B-Instruct") model = PeftModel.from_pretrained(base_model, "SKLP-EDA-LAB/Tesla-Pro-TPI") - Notebooks
- Google Colab
- Kaggle
| module gen_sync ( input clock,input reset,input enable,input [7:0] rate,output wire sync ); | |
| reg [7:0] counter; | |
| assign sync = |(((rate+1)>>1)& counter); | |
| always @(posedge clock) | |
| if(reset || ~enable) | |
| counter <= #1 0; | |
| else if(counter == rate) | |
| counter <= #1 0; | |
| else | |
| counter <= #1 counter + 8'd1; | |
| endmodule | |