Instructions to use tsinghua-sigs-robot-lab/VeriLoop-E2-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use tsinghua-sigs-robot-lab/VeriLoop-E2-GGUF with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf tsinghua-sigs-robot-lab/VeriLoop-E2-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf tsinghua-sigs-robot-lab/VeriLoop-E2-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf tsinghua-sigs-robot-lab/VeriLoop-E2-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf tsinghua-sigs-robot-lab/VeriLoop-E2-GGUF:Q4_K_M

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf tsinghua-sigs-robot-lab/VeriLoop-E2-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf tsinghua-sigs-robot-lab/VeriLoop-E2-GGUF:Q4_K_M

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf tsinghua-sigs-robot-lab/VeriLoop-E2-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf tsinghua-sigs-robot-lab/VeriLoop-E2-GGUF:Q4_K_M

Use Docker

docker model run hf.co/tsinghua-sigs-robot-lab/VeriLoop-E2-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use tsinghua-sigs-robot-lab/VeriLoop-E2-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "tsinghua-sigs-robot-lab/VeriLoop-E2-GGUF"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "tsinghua-sigs-robot-lab/VeriLoop-E2-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/tsinghua-sigs-robot-lab/VeriLoop-E2-GGUF:Q4_K_M

Ollama
How to use tsinghua-sigs-robot-lab/VeriLoop-E2-GGUF with Ollama:
```
ollama run hf.co/tsinghua-sigs-robot-lab/VeriLoop-E2-GGUF:Q4_K_M
```
Unsloth Desktop

How to use tsinghua-sigs-robot-lab/VeriLoop-E2-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf tsinghua-sigs-robot-lab/VeriLoop-E2-GGUF:Q4_K_M

Configure the model in Pi

# Install Pi:
npm install -g @earendil-works/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "tsinghua-sigs-robot-lab/VeriLoop-E2-GGUF:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use tsinghua-sigs-robot-lab/VeriLoop-E2-GGUF with Docker Model Runner:
```
docker model run hf.co/tsinghua-sigs-robot-lab/VeriLoop-E2-GGUF:Q4_K_M
```

Lemonade

How to use tsinghua-sigs-robot-lab/VeriLoop-E2-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull tsinghua-sigs-robot-lab/VeriLoop-E2-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.VeriLoop-E2-GGUF-Q4_K_M

List all available models

lemonade list

Hermes Agent

How to use tsinghua-sigs-robot-lab/VeriLoop-E2-GGUF with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf tsinghua-sigs-robot-lab/VeriLoop-E2-GGUF:Q4_K_M

Configure Hermes

# Install Hermes:
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
hermes setup
# Point Hermes at the local server:
hermes config set model.provider custom
hermes config set model.base_url http://127.0.0.1:8080/v1
hermes config set model.default tsinghua-sigs-robot-lab/VeriLoop-E2-GGUF:Q4_K_M

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use tsinghua-sigs-robot-lab/VeriLoop-E2-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf tsinghua-sigs-robot-lab/VeriLoop-E2-GGUF:Q4_K_M

Configure OpenClaw

# Install OpenClaw:
npm install -g openclaw@latest
# Register the local server and set it as the default model:
openclaw onboard --non-interactive --mode local \
  --auth-choice custom-api-key \
  --custom-base-url http://127.0.0.1:8080/v1 \
  --custom-model-id "tsinghua-sigs-robot-lab/VeriLoop-E2-GGUF:Q4_K_M" \
  --custom-provider-id llama-cpp \
  --custom-compatibility openai \
  --custom-text-input \
  --accept-risk \
  --skip-health

Run OpenClaw

openclaw agent --local --agent main --message "Hello from Hugging Face"

ConorWang commited on 17 days ago

Commit

6b0f211

verified ·

1 Parent(s): 190676a

Delete Q4_RELEASE_IDENTITY.json

Browse files

Files changed (1) hide show

Q4_RELEASE_IDENTITY.json +0 -72

Q4_RELEASE_IDENTITY.json DELETED Viewed

@@ -1,72 +0,0 @@
-{
-  "schema": "veriloop.e2.gguf.q4_k_m.release_identity.v3",
-  "created_at_utc": "2026-09-24T17:15:48.456838+00:00",
-  "tier": "Q4_K_M",
-  "quality_policy": "q4_k_m_v3_root_cause_guided_mixed_precision",
-  "source": "canonical_Veriloop_E2_BF16_GGUF",
-  "direct_from_bf16": true,
-  "low_bit_requantization": false,
-  "main": {
-    "filename": "VeriLoop-E2-Q4_K_M.gguf",
-    "bytes": 19650634496,
-    "sha256": "9291ddca6497eef3eec8cfd5e4e1277a269db6aa236d68ef738f85de63907912",
-    "tensor_count": 851,
-    "effective_bpw": 5.84
-  },
-  "mtp": {
-    "filename": "mtp-VeriLoop-E2-Q4_K_M.gguf",
-    "bytes": 2008056096,
-    "sha256": "0e7f2dfe254f3a5d195d105832411acc1007fd7bb9ac980fe9aae4a1f290d671",
-    "tensor_count": 18,
-    "quantization": "Q4_0"
-  },
-  "precision_policy": {
-    "F32": 353,
-    "Q4_K": 64,
-    "Q5_K": 208,
-    "Q6_K": 226,
-    "Q4_K_tensor_group": "*.ffn_up.weight",
-    "Q5_K_protected_group_added_in_v3": "*.ffn_gate.weight"
-  },
-  "fidelity": {
-    "schema": "veriloop.e2.gguf.q4_k_m.fidelity.v3",
-    "classification": "PASS",
-    "root_cause_intervention": "ffn_gate Q4_K -> Q5_K; ffn_up remains Q4_K",
-    "metrics": {
-      "bf16_mean_ppl": 4.840423,
-      "q4_mean_ppl": 4.86376,
-      "ppl_ratio": 1.004821,
-      "mean_kld": 0.0097,
-      "same_top_p_percent": 96.786,
-      "log_ppl_correlation_percent": 99.76,
-      "rms_delta_p_percent": 2.843
-    },
-    "gates": {
-      "ppl_ratio": "PASS",
-      "mean_kld": "PASS",
-      "same_top_p": "PASS"
-    }
-  },
-  "runtime": {
-    "schema": "veriloop.e2.gguf.q4_k_m.runtime.v3",
-    "created_at_utc": "2026-09-24T17:14:34.962970+00:00",
-    "main_file": "VeriLoop-E2-Q4_K_M.gguf",
-    "mtp_file": "mtp-VeriLoop-E2-Q4_K_M.gguf",
-    "llama_cpp_revision": "42916d83f4a225e56709f873aa8050ac11f5b6a4",
-    "runtime": "stock_llama.cpp",
-    "context_tokens": 8192,
-    "main_gpu_offload": "all_model_layers",
-    "draft_gpu_layers": 0,
-    "main_model_load": "PASS",
-    "main_openai_compatible_generation": "PASS",
-    "mtp_model_load": "PASS",
-    "mtp_openai_compatible_generation": "PASS",
-    "speculative_mode": "draft-mtp",
-    "main_log": "Q4_RUNTIME_MAIN.log",
-    "mtp_log": "Q4_RUNTIME_MTP.log",
-    "runtime_gate": "PASS"
-  },
-  "llama_cpp_revision": "42916d83f4a225e56709f873aa8050ac11f5b6a4",
-  "release_identity": "FROZEN",
-  "public_upload_authorized": true
-}