Instructions to use vxkyyy/vlsi-moe-ffn-merged-formal with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use vxkyyy/vlsi-moe-ffn-merged-formal with Transformers:

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

pipe = pipeline("text-generation", model="vxkyyy/vlsi-moe-ffn-merged-formal")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("vxkyyy/vlsi-moe-ffn-merged-formal")
model = AutoModelForCausalLM.from_pretrained("vxkyyy/vlsi-moe-ffn-merged-formal", device_map="auto")
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 vxkyyy/vlsi-moe-ffn-merged-formal with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/vxkyyy/vlsi-moe-ffn-merged-formal

SGLang

How to use vxkyyy/vlsi-moe-ffn-merged-formal 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 "vxkyyy/vlsi-moe-ffn-merged-formal" \
    --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": "vxkyyy/vlsi-moe-ffn-merged-formal",
		"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 "vxkyyy/vlsi-moe-ffn-merged-formal" \
        --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": "vxkyyy/vlsi-moe-ffn-merged-formal",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use vxkyyy/vlsi-moe-ffn-merged-formal with Docker Model Runner:
```
docker model run hf.co/vxkyyy/vlsi-moe-ffn-merged-formal
```

VLSI-MoE-FFN-Merged-Formal

VLSI Specialist LLM — RTL + Formal Verification Edition Fine-tuned version of vxkyyy/vlsi-moe-ffn-merged specialized for VLSI Formal Verification.

Model Summary

Attribute	Value
Architecture	Qwen2 33B Dense
Parameters	33.8B
Training	LoRA (r=128, α=256), 10 epochs
Data	307 SVA examples
Hardware	AMD Instinct MI300X
Final Loss	0.051

Capabilities

Feature	Base Model	This Model
RTL Generation	✅	✅
Testbenches	✅	✅
SVA Assertions	❌	✅
Coverage Models	❌	✅

Usage

from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained(
    "vxkyyy/vlsi-moe-ffn-merged-formal",
    torch_dtype="auto",
    device_map="auto",
    trust_remote_code=True,
)
tokenizer = AutoTokenizer.from_pretrained(
    "vxkyyy/vlsi-moe-ffn-merged-formal",
    trust_remote_code=True,
)
License
Apache 2.0

Downloads last month: 12

Safetensors

Model size

33B params

Tensor type

BF16

Model tree for vxkyyy/vlsi-moe-ffn-merged-formal

Base model

vxkyyy/vlsi-moe-ffn-merged

Finetuned

(1)

this model