Instructions to use zkaedi/solidity-vuln-auditor-7b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use zkaedi/solidity-vuln-auditor-7b with PEFT:

from peft import PeftModel
from transformers import AutoModelForCausalLM

base_model = AutoModelForCausalLM.from_pretrained("zkaedi/solidity-vuln-auditor-7b")
model = PeftModel.from_pretrained(base_model, "zkaedi/solidity-vuln-auditor-7b")

Transformers

How to use zkaedi/solidity-vuln-auditor-7b with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="zkaedi/solidity-vuln-auditor-7b")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForMultimodalLM

tokenizer = AutoTokenizer.from_pretrained("zkaedi/solidity-vuln-auditor-7b")
model = AutoModelForMultimodalLM.from_pretrained("zkaedi/solidity-vuln-auditor-7b")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use zkaedi/solidity-vuln-auditor-7b with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "zkaedi/solidity-vuln-auditor-7b"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "zkaedi/solidity-vuln-auditor-7b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/zkaedi/solidity-vuln-auditor-7b

SGLang

How to use zkaedi/solidity-vuln-auditor-7b with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "zkaedi/solidity-vuln-auditor-7b" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "zkaedi/solidity-vuln-auditor-7b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "zkaedi/solidity-vuln-auditor-7b" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "zkaedi/solidity-vuln-auditor-7b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Unsloth Studio

How to use zkaedi/solidity-vuln-auditor-7b with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for zkaedi/solidity-vuln-auditor-7b to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for zkaedi/solidity-vuln-auditor-7b to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for zkaedi/solidity-vuln-auditor-7b to start chatting

Load model with FastModel

pip install unsloth
from unsloth import FastModel
model, tokenizer = FastModel.from_pretrained(
    model_name="zkaedi/solidity-vuln-auditor-7b",
    max_seq_length=2048,
)

Docker Model Runner
How to use zkaedi/solidity-vuln-auditor-7b with Docker Model Runner:
```
docker model run hf.co/zkaedi/solidity-vuln-auditor-7b
```

zkaedi commited on Mar 9

Commit

04dad26

verified ·

1 Parent(s): a595746

Retrain 2250ex: bf16 SFT-3ep + DPO-1ep (Trained with Unsloth)

Browse files

Files changed (4) hide show

README.md +3 -0
config.json +47 -7
generation_config.json +10 -0
model.safetensors +3 -0

README.md CHANGED Viewed

@@ -5,6 +5,9 @@ tags:
 - transformers
 - unsloth
 - qwen2
 license: apache-2.0
 language:
 - en

 - transformers
 - unsloth
 - qwen2
+- trl
+- sft
+- dpo
 license: apache-2.0
 language:
 - en

config.json CHANGED Viewed

@@ -2,21 +2,61 @@
   "architectures": [
     "Qwen2ForCausalLM"
   ],
-  "model_type": "qwen2",
   "hidden_size": 3584,
   "intermediate_size": 18944,
   "max_position_embeddings": 32768,
   "max_window_layers": 28,
   "num_attention_heads": 28,
   "num_hidden_layers": 28,
   "num_key_value_heads": 4,
   "rms_norm_eps": 1e-06,
-  "rope_theta": 1000000.0,
-  "sliding_window": 131072,
   "tie_word_embeddings": false,
-  "torch_dtype": "bfloat16",
-  "transformers_version": "4.37.0",
-  "use_cache": true,
   "use_sliding_window": false,
   "vocab_size": 152064
-}

   "architectures": [
     "Qwen2ForCausalLM"
   ],
+  "attention_dropout": 0.0,
+  "bos_token_id": null,
+  "dtype": "bfloat16",
+  "eos_token_id": 151645,
+  "hidden_act": "silu",
   "hidden_size": 3584,
+  "initializer_range": 0.02,
   "intermediate_size": 18944,
+  "layer_types": [
+    "full_attention",
+    "full_attention",
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+    "full_attention",
+    "full_attention",
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+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention"
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   "max_position_embeddings": 32768,
   "max_window_layers": 28,
+  "model_type": "qwen2",
   "num_attention_heads": 28,
   "num_hidden_layers": 28,
   "num_key_value_heads": 4,
+  "pad_token_id": 151665,
   "rms_norm_eps": 1e-06,
+  "rope_parameters": {
+    "rope_theta": 1000000.0,
+    "rope_type": "default"
+  },
+  "sliding_window": null,
   "tie_word_embeddings": false,
+  "transformers_version": "5.2.0",
+  "unsloth_version": "2026.3.4",
+  "use_cache": false,
   "use_sliding_window": false,
   "vocab_size": 152064
+}

generation_config.json ADDED Viewed

	@@ -0,0 +1,10 @@

+{
+  "_from_model_config": true,
+  "eos_token_id": [
+    151645
+  ],
+  "max_length": 32768,
+  "pad_token_id": 151665,
+  "transformers_version": "5.2.0",
+  "use_cache": true
+}

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