model-00001-of-00016.safetensors
Format: LLM-SCAN  ·  Size: 3813.1 MB  ·  Scanned: 2026-07-21  ·  88548 ms
SHA256: c06d95823d60f40a60158d4189c39c13045af863…

Security grade

N/A
Score: 0/100
Artifact Security
N/A / 0
Repository Trust
89 / 100
Deployment Confidence
Low
Artifact Security grades the file. Repository Trust reflects HuggingFace repo metadata signals (license, README, popularity). Deployment Confidence combines both.
Multi-shard GGUF: shard 1 of 16. Header metadata scanned; full tensor analysis requires all shards.

Model info

HuggingFace Provenance

RepositoryAlibaba-NLP/Tongyi-DeepResearch-30B-A3B
File pathmodel-00001-of-00016.safetensors
Repo commit4b0ac5767427a55d08a254f0367e2934976598e0
License (model card)apache-2.0
Pipeline tagtext-generation
README.md✓ present
config.json✓ present
tokenizer_config.json✓ present
Siblings in repo27 file(s)
Downloads7,183
Likes813
Repo trust score
Heuristic 0–100: license + README + config + download/like signals
89/100
Tagstransformers, safetensors, qwen3_moe, text-generation, conversational, en, license:apache-2.0, endpoints_compatible, deploy:azure, region:us
All files in repository (27)
FileSize
.gitattributes 0.0 MB
README.md 0.0 MB
added_tokens.json 0.0 MB
chat_template.jinja 0.0 MB
config.json 0.0 MB
merges.txt 1.6 MB
model-00001-of-00016.safetensors 3813.1 MB
model-00002-of-00016.safetensors 3814.7 MB
model-00003-of-00016.safetensors 3814.7 MB
model-00004-of-00016.safetensors 3814.7 MB
model-00005-of-00016.safetensors 3812.2 MB
model-00006-of-00016.safetensors 3814.7 MB
model-00007-of-00016.safetensors 3814.7 MB
model-00008-of-00016.safetensors 3814.7 MB
model-00009-of-00016.safetensors 3814.7 MB
model-00010-of-00016.safetensors 3812.2 MB
model-00011-of-00016.safetensors 3814.7 MB
model-00012-of-00016.safetensors 3814.7 MB
model-00013-of-00016.safetensors 3814.7 MB
model-00014-of-00016.safetensors 3814.7 MB
model-00015-of-00016.safetensors 3812.2 MB
model-00016-of-00016.safetensors 1026.5 MB
model.safetensors.index.json 1.5 MB
special_tokens_map.json 0.0 MB
tokenizer.json 10.9 MB
tokenizer_config.json 0.0 MB
vocab.json 2.6 MB

Scan coverage

Checks performed
  • Format-specific header parse
  • Supply-chain metadata
  • Runtime compatibility heuristics
  • HuggingFace model card & repository context checked
  • Upstream HuggingFace repository metadata checked
  • Repo identity & commit SHA captured (4b0ac576…)
  • README.md presence checked (✓ present)
  • config.json / tokenizer_config.json presence checked
  • Sibling files enumerated (27 file(s))
  • Downloads / likes / tags captured
  • Full repository file content audit: not performed
  • License legal text validation: not performed
Not covered
  • Runtime execution or dynamic analysis
  • Behavioral backdoor detection
  • Weight-level semantic backdoor detection
  • Full upstream repository verification
  • License validation beyond embedded metadata
  • Malware scanning of surrounding repo files
  • Adversarial robustness or alignment audit
  • Training data provenance
ⓘ Static scanning can detect structural anomalies and known malicious patterns. It cannot guarantee absence of risk. Treat results as a security signal, not a formal audit.
Raw scan data (.llmscan JSON)
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    "quantization": null,
    "scanner_error": null,
    "shard_note": "Multi-shard GGUF: shard 1 of 16. Deep scan requires all shards present; header metadata scanned from shard 1 only."
  },
  "report": {
    "bullets": [
      "Size: 3.72 GB",
      "SHA256: c06d95823d60f40a\u2026"
    ],
    "recommendations": [],
    "summary": "Multi-shard GGUF: shard 1 of 16. Header metadata scanned; full tensor analysis requires all shards."
  },
  "scan_context": {
    "duration_ms": 88548,
    "ended_at": "2026-07-21T13:21:40+00:00Z",
    "limits": {
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      "timeout_ms": 60000
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    "mode": "static-lite",
    "started_at": "2026-07-21T13:21:40+00:00Z"
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  "security": {
    "findings": [],
    "grade": "N/A"
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