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
Download examples/gen_sync.v from SKLP-EDA-LAB/Tesla-Pro-TPI: direct link, hf CLI and curl.
- Browser
- Download file 332 Bytes
-
https://huggingface.co/SKLP-EDA-LAB/Tesla-Pro-TPI/resolve/main/examples/gen_sync.v
- Command line
-
hf download hf://SKLP-EDA-LAB/Tesla-Pro-TPI/examples/gen_sync.v
-
curl -L -o gen_sync.v https://huggingface.co/SKLP-EDA-LAB/Tesla-Pro-TPI/resolve/main/examples/gen_sync.v
332 Bytes
| 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 | |