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---
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language:
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- en
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metrics:
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- code_eval
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base_model:
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- deepseek-ai/deepseek-coder-6.7b-base
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pipeline_tag: text-generation
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library_name: transformers
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tags:
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- code
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---
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# AssertSolver |
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<!-- Provide a quick summary of what the model is/does. --> |
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## Model Details |
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### Model Description |
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<!-- Provide a longer summary of what this model is. --> |
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- **Finetuned from model:** deepseek-ai/deepseek-coder-6.7b-base |
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### Model Sources |
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<!-- Provide the basic links for the model. --> |
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- **Paper:** Insights from Rights and Wrongs: A Large Language Model for Solving Assertion Failures in RTL Design |
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## How to Get Started with the Model |
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Use the code below to get started with the model. |
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``` |
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from transformers import AutoTokenizer, AutoModelForCausalLM |
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import torch |
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model_name = "1412312anonymous/AssertSolver" |
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tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True) |
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model = AutoModelForCausalLM.from_pretrained(model_name, trust_remote_code=True, torch_dtype=torch.bfloat16).cuda() |
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prompt = "Tell me how to fix the bugs inside: `always(*) // Pretend that this * should be rst`" |
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messages = [{"role": "user", "content": prompt}] |
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inputs = tokenizer.apply_chat_template(messages, add_generation_prompt=True, return_tensors="pt").to(model.device) |
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outputs = model.generate( |
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inputs, |
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max_new_tokens=512, |
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do_sample=False, |
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top_k=50, |
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top_p=0.95, |
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num_return_sequences=1, |
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eos_token_id=tokenizer.eos_token_id, |
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) |
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print(tokenizer.decode(outputs[0][len(inputs[0]) :], skip_special_tokens=True)) |
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``` |
