deepseek-r1-distill-qwen-1.5b-base/README.md

license, pipeline_tag, library_name

license	pipeline_tag	library_name
mit	text-generation	transformers

DeepSeek-R1-Distill-Qwen-1.5B Obfuscated Reviewer Package

This repository contains the AloePri obfuscated DeepSeek-R1-Distill-Qwen-1.5B reviewer package.

Anonymous reviewer link:

https://anonymous-hf.up.railway.app/a/9e43t2oh6gmq/

Repository Structure

.
|-- README.md
|-- LICENSE
|-- UPSTREAM_README.md
|-- SHA256SUMS
|-- config.json
|-- configuration.json
|-- generation_config.json
|-- model.safetensors.index.json
|-- model-00001-of-00008.safetensors
|-- model-00002-of-00008.safetensors
|-- model-00003-of-00008.safetensors
|-- model-00004-of-00008.safetensors
|-- model-00005-of-00008.safetensors
|-- model-00006-of-00008.safetensors
|-- model-00007-of-00008.safetensors
|-- model-00008-of-00008.safetensors
|-- tokenizer.json
|-- tokenizer_config.json
`-- client/
    `-- client_secret.pt

Usage

Download the repository contents from the anonymous reviewer link and place the directory under:

models/deepseek-r1-distill-qwen-1.5b-obfuscated-reviewer/

The runtime configuration should use:

model_path=models/deepseek-r1-distill-qwen-1.5b-obfuscated-reviewer
client_secret_path=models/deepseek-r1-distill-qwen-1.5b-obfuscated-reviewer/client/client_secret.pt

Minimal dependency set:

pip install torch transformers accelerate safetensors

Basic local loading check:

from transformers import AutoModelForCausalLM, AutoTokenizer

model_path = "models/deepseek-r1-distill-qwen-1.5b-obfuscated-reviewer"
tokenizer = AutoTokenizer.from_pretrained(model_path, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(
    model_path,
    device_map="auto",
    torch_dtype="auto",
    trust_remote_code=True,
)
client_secret_path = f"{model_path}/client/client_secret.pt"

Included Files

• sharded safetensors model weights
• model.safetensors.index.json
• tokenizer files
• model configuration files
• client/client_secret.pt for reviewer-side input mapping and output recovery
• upstream license and README preserved for model-license review

Excluded Files

• deployment .env files
• private hostnames, private IP addresses, logs, and databases
• local training paths and account identifiers

Runtime loaders should set the model path to the repository root and the client secret path to client/client_secret.pt.