Text Generation
PEFT
Safetensors
English
lora
grpo
reinforcement-learning
verilog
systemverilog
hardware-verification
conversational
Instructions to use scale-lab/CovR-Qwen2.5-Coder-7B-Instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use scale-lab/CovR-Qwen2.5-Coder-7B-Instruct 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, "scale-lab/CovR-Qwen2.5-Coder-7B-Instruct") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from scale-lab/CovR-Qwen2.5-Coder-7B-Instruct: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/scale-lab/CovR-Qwen2.5-Coder-7B-Instruct/resolve/main/tokenizer.json
- Command line
-
hf download hf://scale-lab/CovR-Qwen2.5-Coder-7B-Instruct/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/scale-lab/CovR-Qwen2.5-Coder-7B-Instruct/resolve/main/tokenizer.json
11.4 MB
- Xet hash:
- 914e66a591451b2ad717503a04314cc87b30fff60b856169641a370111fb1d65
- Size of remote file:
- 11.4 MB
- SHA256:
- 3ce73a62b1248faacdbd15e69ceee84dfe9308357dba024cadd2ed1ea79b6dd4
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