Instructions to use rvcarung/ProxyType-9B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use rvcarung/ProxyType-9B with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3.5-9B") model = PeftModel.from_pretrained(base_model, "rvcarung/ProxyType-9B") - Notebooks
- Google Colab
- Kaggle
Download model-info.json from rvcarung/ProxyType-9B: direct link, hf CLI and curl.
- Browser
- Download file 4.08 kB
-
https://huggingface.co/rvcarung/ProxyType-9B/resolve/main/model-info.json
- Command line
-
hf download hf://rvcarung/ProxyType-9B/model-info.json
-
curl -L -o model-info.json https://huggingface.co/rvcarung/ProxyType-9B/resolve/main/model-info.json
4.08 kB
| { | |
| "schema_version": "proxybench-hub-adapter-v1", | |
| "name": "ProxyType-9B", | |
| "format": "PEFT LoRA adapter", | |
| "base_model": "Qwen/Qwen3.5-9B", | |
| "base_revision": "c202236235762e1c871ad0ccb60c8ee5ba337b9a", | |
| "files": { | |
| "adapter_config.json": "0647748b38619f477c82abe5d39125cc40df52ad0df224abc29c2616e13aa6fc", | |
| "adapter_model.safetensors": "88af0f9aeacc934a6bc054fa0943443e2d2b13f30fc25e38a141907859280a89", | |
| "chat_template.jinja": "a4aee8afcf2e0711942cf848899be66016f8d14a889ff9ede07bca099c28f715", | |
| "tokenizer.json": "87a7830d63fcf43bf241c3c5242e96e62dd3fdc29224ca26fed8ea333db72de4", | |
| "tokenizer_config.json": "34d105465eea1e580480ed25708ac08b2e1dce7af6d8742f3c3ae5fdf5927728", | |
| "model-system-prompt.txt": "fb828305c494f90092180ae4e0dea4290b00f7f90fbb47ec34f8dff1810f3a93", | |
| "LICENSE.base-model": "bbedc3fda3305820b977265f01b8619d87570a6739de3a5582c3464840f1e57a", | |
| "NOTICE": "f1d88f508dd31d46cee4a91a3fa847c458a8623550867dd2b722099ba1397d03", | |
| "README.md": "6389cee6196050e3cf5c81b47e8f9478e424dc48c13992ab399d98e8100da413" | |
| }, | |
| "system_prompt": "model-system-prompt.txt", | |
| "prompt_sha256": "fb828305c494f90092180ae4e0dea4290b00f7f90fbb47ec34f8dff1810f3a93", | |
| "training": { | |
| "examples": 330, | |
| "development_examples": 90, | |
| "source_files": 36, | |
| "epochs": 2, | |
| "updates": 660, | |
| "rank": 8, | |
| "alpha": 16, | |
| "dropout": 0, | |
| "learning_rate": 0.0001, | |
| "batch_size": 1, | |
| "gradient_accumulation": 1, | |
| "context_tokens": 5120, | |
| "input_tokens": 3328, | |
| "response_tokens": 1792 | |
| }, | |
| "software_versions": { | |
| "huggingface_hub": "1.31.0", | |
| "peft": "0.21.0", | |
| "transformers": "5.5.0", | |
| "safetensors": "0.8.0", | |
| "unsloth": "2026.9.4", | |
| "unsloth_zoo": "2026.9.3", | |
| "torch": "2.12.1" | |
| }, | |
| "load_validation": { | |
| "status": "COMPLETE", | |
| "validated_at": "2026-09-30T04:13:10.923714+00:00", | |
| "adapter_sha256": "88af0f9aeacc934a6bc054fa0943443e2d2b13f30fc25e38a141907859280a89", | |
| "base_model": "Qwen/Qwen3.5-9B", | |
| "base_revision": "c202236235762e1c871ad0ccb60c8ee5ba337b9a", | |
| "exact_adapter_tensors": true, | |
| "adapter_requests": [ | |
| { | |
| "format": "adapter", | |
| "source": "text", | |
| "status": "COMPLETE", | |
| "output_tokens": 651, | |
| "answer_sha256": "5f72c2d7ba1b7f20eb4da647cbefbf4c05f6a297ff2cff05989124e01ade3be7" | |
| }, | |
| { | |
| "format": "adapter", | |
| "source": "html", | |
| "status": "COMPLETE", | |
| "output_tokens": 623, | |
| "answer_sha256": "08a07e32781c3dbb7383ee300e49aed7cbff362755f3864ac9b914805590a059" | |
| } | |
| ], | |
| "accuracy_assessed": false, | |
| "retained_evidence_sha256": "5f535f23c889a90669b77cd7f239a41838fb778f1924645c3b41897c3b2f02e5", | |
| "interpretation": "Saved local loading evidence. Other environments remain untested." | |
| }, | |
| "development_evaluation": { | |
| "status": "COMPLETE", | |
| "scorer": "source-cells-v1", | |
| "dataset_split": "development", | |
| "targets": 90, | |
| "evaluated_format": "Merged BF16/F32 GGUF", | |
| "evaluated_model_sha256": "fad63488e992191f83d6565d2ac2b34e01eccfaef971e2936a53a32188e55c24", | |
| "aggregate": { | |
| "format_valid": 90, | |
| "exact": 8, | |
| "source_value_correct": 89, | |
| "fields": { | |
| "reporting_scope": 90, | |
| "series_identifiers": 90, | |
| "issuer_name": 90, | |
| "security_identifiers": 90, | |
| "ticker": 90, | |
| "meeting_date": 90, | |
| "meeting_type": 90, | |
| "proposal_number": 90, | |
| "raw_description": 90, | |
| "separate_subject": 90, | |
| "proposal_source": 90, | |
| "participation": 90, | |
| "vote_components": 90, | |
| "management_recommendation": 89 | |
| }, | |
| "origin_errors": 0, | |
| "derivation_errors": 1, | |
| "unsupported_quotes": 0, | |
| "quotation_errors": 1 | |
| }, | |
| "retained_report_sha256": "9326a8dabd3a1635bddae528f442909705ad7946990067f89245a56ced296638", | |
| "interpretation": "Exposed development references. These merged-model scores do not establish direct adapter accuracy." | |
| }, | |
| "public_release": "public", | |
| "adapter_public_license": "not selected" | |
| } | |