Instructions to use Blackfrost-Research/GLM-5.3-F.U-AnthraClaud-Edition-BF16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Blackfrost-Research/GLM-5.3-F.U-AnthraClaud-Edition-BF16 with Transformers:

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

pipe = pipeline("text-generation", model="Blackfrost-Research/GLM-5.3-F.U-AnthraClaud-Edition-BF16")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Blackfrost-Research/GLM-5.3-F.U-AnthraClaud-Edition-BF16")
model = AutoModelForCausalLM.from_pretrained("Blackfrost-Research/GLM-5.3-F.U-AnthraClaud-Edition-BF16", 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 Blackfrost-Research/GLM-5.3-F.U-AnthraClaud-Edition-BF16 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Blackfrost-Research/GLM-5.3-F.U-AnthraClaud-Edition-BF16"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Blackfrost-Research/GLM-5.3-F.U-AnthraClaud-Edition-BF16",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Blackfrost-Research/GLM-5.3-F.U-AnthraClaud-Edition-BF16

SGLang

How to use Blackfrost-Research/GLM-5.3-F.U-AnthraClaud-Edition-BF16 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 "Blackfrost-Research/GLM-5.3-F.U-AnthraClaud-Edition-BF16" \
    --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": "Blackfrost-Research/GLM-5.3-F.U-AnthraClaud-Edition-BF16",
		"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 "Blackfrost-Research/GLM-5.3-F.U-AnthraClaud-Edition-BF16" \
        --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": "Blackfrost-Research/GLM-5.3-F.U-AnthraClaud-Edition-BF16",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use Blackfrost-Research/GLM-5.3-F.U-AnthraClaud-Edition-BF16 with Docker Model Runner:
```
docker model run hf.co/Blackfrost-Research/GLM-5.3-F.U-AnthraClaud-Edition-BF16
```

Blackfrost-AI commited on 2 days ago

Commit

45e8d60

verified ·

1 Parent(s): eac6aa0

Remove paid-access pricing from model card; retain upstream GLM license

Browse files

Files changed (1) hide show

README.md +3 -11

README.md CHANGED Viewed

@@ -1,6 +1,6 @@
 ---
 license: other
-license_name: blackfrost-commercial
 base_model:
   - zai-org/GLM-5.3-BF16
 base_model_relation: finetune
@@ -33,7 +33,6 @@ tags:
 **Built by [Blackfrost](https://x.com/Blackfrost_AI) · Las Vegas, Nevada**
 ![BF16](https://img.shields.io/badge/Format-BF16-047857?style=for-the-badge)
-![Commercial](https://img.shields.io/badge/License-Commercial-b45309?style=for-the-badge)
 ![Weights](https://img.shields.io/badge/Status-WEIGHTS_LIVE-047857?style=for-the-badge)
 **FREE THANKS TO ANTHROPIC LYING ON OUR MODELS**
 </div>
@@ -42,11 +41,7 @@ tags:
 > model shards plus three preserved MTP shards, with its configuration,
 > tokenizer, generation settings, and native GLM chat template.
-## Licensed access — $599 USD
-This checkpoint is offered under a Blackfrost commercial license for **$599 USD**.
-Purchase, access, and enterprise licensing information is available from the
-[Blackfrost model catalog](https://redpillreader.com/models).
 Access is intended for security firms, authorized red teams, AI-safety labs,
 guardrail and detection teams, and enterprise research groups operating in
@@ -117,16 +112,13 @@ of the final judged evaluation. Results will be added only after qualification.
   independently in the selected runtime.
 - GLM-5.3's recommended sampling baseline is temperature `1.0` and top-p `0.95`.
-## Access and licensing
-The Blackfrost derivative is distributed under a separate commercial agreement.
 Recipients remain responsible for compliance with applicable upstream terms,
 export controls, local law, and their own authorization boundaries.
 The upstream checkpoint remains subject to the
 [`GLM-5.3 License`](https://huggingface.co/zai-org/GLM-5.3-BF16/blob/main/LICENSE).
-**[Purchase or request licensed access — $599 USD](https://redpillreader.com/models)**
 For air-gapped deployment, enterprise support, evaluation services, or a custom
 build, contact [@Blackfrost_AI](https://x.com/Blackfrost_AI).

 ---
 license: other
+license_name: glm-5.3
 base_model:
   - zai-org/GLM-5.3-BF16
 base_model_relation: finetune
 **Built by [Blackfrost](https://x.com/Blackfrost_AI) · Las Vegas, Nevada**
 ![BF16](https://img.shields.io/badge/Format-BF16-047857?style=for-the-badge)
 ![Weights](https://img.shields.io/badge/Status-WEIGHTS_LIVE-047857?style=for-the-badge)
 **FREE THANKS TO ANTHROPIC LYING ON OUR MODELS**
 </div>
 > model shards plus three preserved MTP shards, with its configuration,
 > tokenizer, generation settings, and native GLM chat template.
+## Intended audience
 Access is intended for security firms, authorized red teams, AI-safety labs,
 guardrail and detection teams, and enterprise research groups operating in
   independently in the selected runtime.
 - GLM-5.3's recommended sampling baseline is temperature `1.0` and top-p `0.95`.
+## License and support
 Recipients remain responsible for compliance with applicable upstream terms,
 export controls, local law, and their own authorization boundaries.
 The upstream checkpoint remains subject to the
 [`GLM-5.3 License`](https://huggingface.co/zai-org/GLM-5.3-BF16/blob/main/LICENSE).
 For air-gapped deployment, enterprise support, evaluation services, or a custom
 build, contact [@Blackfrost_AI](https://x.com/Blackfrost_AI).