Text Generation
Transformers
ONNX
Safetensors
English
gpt2
chess
pgn
causal-lm
game-playing
text-generation-inference
Instructions to use InterwebAlchemy/kn1ght-bullet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use InterwebAlchemy/kn1ght-bullet with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="InterwebAlchemy/kn1ght-bullet")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("InterwebAlchemy/kn1ght-bullet") model = AutoModelForCausalLM.from_pretrained("InterwebAlchemy/kn1ght-bullet", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use InterwebAlchemy/kn1ght-bullet with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "InterwebAlchemy/kn1ght-bullet" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "InterwebAlchemy/kn1ght-bullet", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/InterwebAlchemy/kn1ght-bullet
- SGLang
How to use InterwebAlchemy/kn1ght-bullet 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 "InterwebAlchemy/kn1ght-bullet" \ --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": "InterwebAlchemy/kn1ght-bullet", "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 "InterwebAlchemy/kn1ght-bullet" \ --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": "InterwebAlchemy/kn1ght-bullet", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use InterwebAlchemy/kn1ght-bullet with Docker Model Runner:
docker model run hf.co/InterwebAlchemy/kn1ght-bullet
Upload folder using huggingface_hub
Browse files- .gitattributes +2 -0
- LICENSE +34 -0
- README.md +11 -3
- assets/kn1ght-bullet.png +3 -0
- assets/tokenizer-comparison.png +3 -0
.gitattributes
CHANGED
|
@@ -33,3 +33,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
|
|
| 33 |
*.zip filter=lfs diff=lfs merge=lfs -text
|
| 34 |
*.zst filter=lfs diff=lfs merge=lfs -text
|
| 35 |
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
|
|
|
|
|
|
|
|
| 33 |
*.zip filter=lfs diff=lfs merge=lfs -text
|
| 34 |
*.zst filter=lfs diff=lfs merge=lfs -text
|
| 35 |
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
| 36 |
+
assets/kn1ght-bullet.png filter=lfs diff=lfs merge=lfs -text
|
| 37 |
+
assets/tokenizer-comparison.png filter=lfs diff=lfs merge=lfs -text
|
LICENSE
ADDED
|
@@ -0,0 +1,34 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
Creative Commons Attribution 4.0 International (CC BY 4.0)
|
| 2 |
+
|
| 3 |
+
Copyright 2026 InterwebAlchemy
|
| 4 |
+
|
| 5 |
+
You are free to:
|
| 6 |
+
|
| 7 |
+
Share — copy and redistribute the material in any medium or format for any purpose,
|
| 8 |
+
even commercially.
|
| 9 |
+
|
| 10 |
+
Adapt — remix, transform, and build upon the material for any purpose, even
|
| 11 |
+
commercially.
|
| 12 |
+
|
| 13 |
+
The licensor cannot revoke these freedoms as long as you follow the license terms.
|
| 14 |
+
|
| 15 |
+
Under the following terms:
|
| 16 |
+
|
| 17 |
+
Attribution — You must give appropriate credit, provide a link to the license, and
|
| 18 |
+
indicate if changes were made. You may do so in any reasonable manner,
|
| 19 |
+
but not in any way that suggests the licensor endorses you or your use.
|
| 20 |
+
|
| 21 |
+
No additional restrictions — You may not apply legal terms or technological measures
|
| 22 |
+
that legally restrict others from doing anything the
|
| 23 |
+
license permits.
|
| 24 |
+
|
| 25 |
+
Notices:
|
| 26 |
+
|
| 27 |
+
You do not have to comply with the license for elements of the material in the public
|
| 28 |
+
domain or where your use is permitted by an applicable exception or limitation.
|
| 29 |
+
|
| 30 |
+
No warranties are given. The license may not give you all of the permissions necessary
|
| 31 |
+
for your intended use. For example, other rights such as publicity, privacy, or moral
|
| 32 |
+
rights may limit how you use the material.
|
| 33 |
+
|
| 34 |
+
Full license text: https://creativecommons.org/licenses/by/4.0/legalcode
|
README.md
CHANGED
|
@@ -1,7 +1,7 @@
|
|
| 1 |
---
|
| 2 |
language:
|
| 3 |
- en
|
| 4 |
-
license:
|
| 5 |
tags:
|
| 6 |
- chess
|
| 7 |
- pgn
|
|
@@ -10,10 +10,16 @@ tags:
|
|
| 10 |
- game-playing
|
| 11 |
library_name: transformers
|
| 12 |
pipeline_tag: text-generation
|
|
|
|
|
|
|
|
|
|
|
|
|
| 13 |
---
|
| 14 |
|
| 15 |
# kn1ght-bullet
|
| 16 |
|
|
|
|
|
|
|
| 17 |
A 4.3M parameter GPT trained to play chess by next-token prediction on PGN notation.
|
| 18 |
Intended for use in chess tutoring applications via constrained decoding at inference time.
|
| 19 |
|
|
@@ -40,9 +46,11 @@ for the large majority of positions.
|
|
| 40 |
|
| 41 |
## Training Pipeline
|
| 42 |
|
| 43 |
-
Training proceeded in three phases
|
| 44 |
[InterwebAlchemy/pgn-dataset-including-special-tokens](https://huggingface.co/datasets/InterwebAlchemy/pgn-dataset-including-special-tokens)
|
| 45 |
-
|
|
|
|
|
|
|
| 46 |
|
| 47 |
**Phase 1 — Pre-training**
|
| 48 |
200,000 steps on 100,000 games. The model learns PGN structure and develops opening
|
|
|
|
| 1 |
---
|
| 2 |
language:
|
| 3 |
- en
|
| 4 |
+
license: cc-by-4.0
|
| 5 |
tags:
|
| 6 |
- chess
|
| 7 |
- pgn
|
|
|
|
| 10 |
- game-playing
|
| 11 |
library_name: transformers
|
| 12 |
pipeline_tag: text-generation
|
| 13 |
+
datasets:
|
| 14 |
+
- InterwebAlchemy/pgn-dataset
|
| 15 |
+
- InterwebAlchemy/pgn-dataset-including-special-tokens
|
| 16 |
+
thumbnail: https://huggingface.co/InterwebAlchemy/kn1ght-bullet/resolve/main/kn1ght-bullet.png
|
| 17 |
---
|
| 18 |
|
| 19 |
# kn1ght-bullet
|
| 20 |
|
| 21 |
+

|
| 22 |
+
|
| 23 |
A 4.3M parameter GPT trained to play chess by next-token prediction on PGN notation.
|
| 24 |
Intended for use in chess tutoring applications via constrained decoding at inference time.
|
| 25 |
|
|
|
|
| 46 |
|
| 47 |
## Training Pipeline
|
| 48 |
|
| 49 |
+
Training proceeded in three phases. Pre-training used
|
| 50 |
[InterwebAlchemy/pgn-dataset-including-special-tokens](https://huggingface.co/datasets/InterwebAlchemy/pgn-dataset-including-special-tokens)
|
| 51 |
+
(~3.5M games, average ELO ~2240, spanning 1783–2006), derived from the base
|
| 52 |
+
[InterwebAlchemy/pgn-dataset](https://huggingface.co/datasets/InterwebAlchemy/pgn-dataset)
|
| 53 |
+
which adds `[g_start]` / `[g_end]` game boundary tokens.
|
| 54 |
|
| 55 |
**Phase 1 — Pre-training**
|
| 56 |
200,000 steps on 100,000 games. The model learns PGN structure and develops opening
|
assets/kn1ght-bullet.png
ADDED
|
Git LFS Details
|
assets/tokenizer-comparison.png
ADDED
|
Git LFS Details
|