Instructions to use reaperdoesntknow/DistilQwen3-1.7B-uncensored with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use reaperdoesntknow/DistilQwen3-1.7B-uncensored with Transformers:

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

pipe = pipeline("text-generation", model="reaperdoesntknow/DistilQwen3-1.7B-uncensored")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("reaperdoesntknow/DistilQwen3-1.7B-uncensored")
model = AutoModelForCausalLM.from_pretrained("reaperdoesntknow/DistilQwen3-1.7B-uncensored", 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 reaperdoesntknow/DistilQwen3-1.7B-uncensored with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "reaperdoesntknow/DistilQwen3-1.7B-uncensored"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "reaperdoesntknow/DistilQwen3-1.7B-uncensored",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/reaperdoesntknow/DistilQwen3-1.7B-uncensored

SGLang

How to use reaperdoesntknow/DistilQwen3-1.7B-uncensored 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 "reaperdoesntknow/DistilQwen3-1.7B-uncensored" \
    --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": "reaperdoesntknow/DistilQwen3-1.7B-uncensored",
		"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 "reaperdoesntknow/DistilQwen3-1.7B-uncensored" \
        --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": "reaperdoesntknow/DistilQwen3-1.7B-uncensored",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use reaperdoesntknow/DistilQwen3-1.7B-uncensored with Docker Model Runner:
```
docker model run hf.co/reaperdoesntknow/DistilQwen3-1.7B-uncensored
```

reaperdoesntknow commited on Mar 30

Commit

f400d13

verified ·

1 Parent(s): a7b2e87

Add DISC Mathematical Foundations, update portfolio stats (49 models, 22,598 total downloads)

Browse files

Files changed (1) hide show

README.md +10 -3

README.md CHANGED Viewed

@@ -207,7 +207,14 @@ Carbon emissions can be estimated using the [Machine Learning Impact calculator]
 *Part of the [DistilQwen3 Series](https://huggingface.co/reaperdoesntknow) by [Convergent Intelligence LLC: Research Division](https://huggingface.co/reaperdoesntknow)*
-### Related Models
 | Model | Downloads | Format |
 |-------|-----------|--------|
@@ -254,6 +261,6 @@ Full methodology: [Structure Over Scale (DOI: 10.57967/hf/8165)](https://doi.org
 <!-- DISTILQWEN-SPOTLIGHT-END -->
 ---
-<sub>Part of the [reaperdoesntknow research portfolio](https://huggingface.co/reaperdoesntknow) — 48 models, 12,094 total downloads | Last refreshed: 2026-03-29 21:05 UTC</sub>
-<!-- cix-keeper-ts:2026-03-30T02:42:39Z -->
 <!-- card-refresh: 2026-03-30 -->

 *Part of the [DistilQwen3 Series](https://huggingface.co/reaperdoesntknow) by [Convergent Intelligence LLC: Research Division](https://huggingface.co/reaperdoesntknow)*
+#
+## Mathematical Foundations: Discrepancy Calculus (DISC)
+This model is part of a distillation chain built on Discrepancy Calculus — a measure-theoretic framework where the teacher's output distribution is decomposed via the Mesh Fundamental Identity into smooth (AC), jump, and Cantor components. The discrepancy operator $Df(x) = \lim_{\varepsilon \downarrow 0} \frac{1}{\varepsilon} \int_x^{x+\varepsilon} \frac{|f(t) - f(x)|}{|t - x|} dt$ quantifies local structural mismatch that standard KL divergence averages away.
+Full theory: *"On the Formal Analysis of Discrepancy Calculus"* (Colca, 2026; Convergent Intelligence LLC: Research Division). Full methodology: [Structure Over Scale (DOI: 10.57967/hf/8165)](https://doi.org/10.57967/hf/8165).
+## Related Models
 | Model | Downloads | Format |
 |-------|-----------|--------|
 <!-- DISTILQWEN-SPOTLIGHT-END -->
 ---
+<sub>Part of the [reaperdoesntknow research portfolio](https://huggingface.co/reaperdoesntknow) — 49 models, 22,598 total downloads | Last refreshed: 2026-03-30 12:05 UTC</sub>
+<!-- cix-keeper-ts:2026-03-30T12:05:00Z -->
 <!-- card-refresh: 2026-03-30 -->