Instructions to use Bochkov/ab_ext_binary16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Bochkov/ab_ext_binary16 with Transformers:

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

pipe = pipeline("text-generation", model="Bochkov/ab_ext_binary16", trust_remote_code=True)

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("Bochkov/ab_ext_binary16", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Bochkov/ab_ext_binary16 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Bochkov/ab_ext_binary16"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Bochkov/ab_ext_binary16",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Bochkov/ab_ext_binary16

SGLang

How to use Bochkov/ab_ext_binary16 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 "Bochkov/ab_ext_binary16" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Bochkov/ab_ext_binary16",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

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 "Bochkov/ab_ext_binary16" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Bochkov/ab_ext_binary16",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Bochkov/ab_ext_binary16 with Docker Model Runner:
```
docker model run hf.co/Bochkov/ab_ext_binary16
```

Bochkov commited on 5 days ago

Commit

f32b191

verified ·

1 Parent(s): 2c006ab

Update README.md

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README.md +18 -0

README.md CHANGED Viewed

@@ -318,3 +318,21 @@ or configuration.
 ## Attribution and licensing
 Tokenizer artifacts are sourced from `HuggingFaceTB/SmolLM2-1.7B`.

 ## Attribution and licensing
 Tokenizer artifacts are sourced from `HuggingFaceTB/SmolLM2-1.7B`.
+---
+## 🧑‍🔬 Citation & Concept
+If you use this model or the underlying concepts in your research, please cite our work:
+```
+@misc{bochkov2026languagemodelsneedtrainable,
+      title={Do Language Models Need a Trainable Input Embedding Table? Fixed Minimal Token Codes at 1.7B-Class Scale},
+      author={A. Bochkov},
+      year={2026},
+      eprint={2610.04002},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL},
+      url={https://arxiv.org/abs/2610.04002},
+}
+```