Instructions to use SecludedCorner/bind2_0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SecludedCorner/bind2_0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="SecludedCorner/bind2_0", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("SecludedCorner/bind2_0", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use SecludedCorner/bind2_0 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "SecludedCorner/bind2_0" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "SecludedCorner/bind2_0", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/SecludedCorner/bind2_0
- SGLang
How to use SecludedCorner/bind2_0 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 "SecludedCorner/bind2_0" \ --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": "SecludedCorner/bind2_0", "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 "SecludedCorner/bind2_0" \ --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": "SecludedCorner/bind2_0", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use SecludedCorner/bind2_0 with Docker Model Runner:
docker model run hf.co/SecludedCorner/bind2_0
bind2_0 — delta-rule backbone with a forced bottleneck
Gated-delta-rule backbone; the parameter-matching reference for the bind2_1 arms.
Research artifact. Not a competition entry.
What this is
A frozen snapshot of the code for one model generation. It is not a living repository: it is never updated after release. Files shared with another generation are duplicated here on purpose, so that the code closure is complete and nothing has to be fetched from a sibling package.
Self-contained in code, not in data. Every module the code imports ships here. Large or non-redistributable inputs -- corpora, official evaluation sets, token streams -- do not, and are listed under "Inputs you must supply" in BUILD.md with how to obtain or regenerate each. Do not read the completeness of src/ as a claim that the package runs with no further downloads.
Contents
| count | |
|---|---|
source files (src/) |
2 |
shipped data (data/) |
1 |
| externally-obtained inputs | 1 |
MANIFEST.json records, for every artifact, its original path in the working tree, its SHA-256, its size, and the git commit it came from. That is the traceability record: it is what lets you prove which state of the code produced a published result.
External inputs (not redistributed here)
alaya-strict-small/tokens_u16.bin— regenerable from the bind1 package's tokenizer chain
Building and running
See BUILD.md. It states plainly what works, what does not, and why.
Availability of this package
If a model card, paper or dataset page points at this package, that pointer must resolve for whoever reads it. A public card that links private code makes a reproducibility promise it cannot keep — and a licence line on unreachable code claims a release that has not happened. Before publishing any pointer to this package, confirm the package is actually reachable by the audience that will read the pointer.
Licence
MIT (see LICENSE). Code only — model weights and evaluation artifacts are distributed separately and carry their own terms.