Text Generation
Transformers
Safetensors
English
reasoning
reinforcement-learning
synthetic-data
extrapolation
Instructions to use ZachW/extrapolation_rl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ZachW/extrapolation_rl with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="ZachW/extrapolation_rl")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ZachW/extrapolation_rl", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use ZachW/extrapolation_rl with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "ZachW/extrapolation_rl" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ZachW/extrapolation_rl", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/ZachW/extrapolation_rl
- SGLang
How to use ZachW/extrapolation_rl 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 "ZachW/extrapolation_rl" \ --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": "ZachW/extrapolation_rl", "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 "ZachW/extrapolation_rl" \ --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": "ZachW/extrapolation_rl", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use ZachW/extrapolation_rl with Docker Model Runner:
docker model run hf.co/ZachW/extrapolation_rl
Upload extrapolation artifact: 050302 README
Browse files- 050302/README.md +64 -0
050302/README.md
ADDED
|
@@ -0,0 +1,64 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
# Extrapolation Release Checkpoints
|
| 2 |
+
|
| 3 |
+
This release contains the 020305 and 050302 extrapolation checkpoint batches for the Interplay-LM-Reasoning project. The checkpoints are organized together in one Hugging Face repository rather than as separate model repositories.
|
| 4 |
+
|
| 5 |
+
## Layout
|
| 6 |
+
|
| 7 |
+
```text
|
| 8 |
+
020305/
|
| 9 |
+
README.md
|
| 10 |
+
pretrain/checkpoint-18809/
|
| 11 |
+
rl/op11_14_step200/
|
| 12 |
+
rl/op13_20_step200/
|
| 13 |
+
rl/op15_20_step200/
|
| 14 |
+
opd_refkl/op11_14_step200/
|
| 15 |
+
evals/
|
| 16 |
+
050302/
|
| 17 |
+
README.md
|
| 18 |
+
pretrain/checkpoint-18586/
|
| 19 |
+
rl/op11_14_step200/
|
| 20 |
+
rl/op13_20_step200/
|
| 21 |
+
rl/op15_20_step200/
|
| 22 |
+
opd_refkl/op13_20_step200/
|
| 23 |
+
evals/
|
| 24 |
+
```
|
| 25 |
+
|
| 26 |
+
The default upload includes compact evaluation files: `summary.csv`, `summary.json`, per-model `*_metrics.json`, graph `results.json`, and score reports. Raw generation JSONL files and per-sample graph-result JSONL files are large and are uploaded when the upload helper is run with `--include-generations` and `--include-per-sample-results`.
|
| 27 |
+
|
| 28 |
+
## Run Index
|
| 29 |
+
|
| 30 |
+
| Model path | Exp name | Script/config | Model name | Time |
|
| 31 |
+
| --- | --- | --- | --- | --- |
|
| 32 |
+
| `020305/pretrain/checkpoint-18809` | `interplay_fig3_pretrain_arkeng_h100x4_r12` | `scripts/arnold/launch_fig3_pretrain_h100x4_arkeng_r12.yaml` | `pretrain_ckpt18809` | 2026-08-14 23:57:05 to 2026-08-15 05:48:41 UTC |
|
| 33 |
+
| `020305/rl/op11_14_step200` | `interplay_rl_ckpt18809_op11_14_arkeng_a100x8_r62` | `scripts/arnold/launch_rl_ckpt18809_op11_14_a100x8_arkeng_r62.yaml` | `rl_ckpt18809_op11_14_step200_merged_hf` | 2026-08-20 12:20:11 to 14:50:50 UTC |
|
| 34 |
+
| `020305/rl/op13_20_step200` | `interplay_rl_ckpt18809_op13_20_arkeng_a100x8_r62` | `scripts/arnold/launch_rl_ckpt18809_op13_20_a100x8_arkeng_r62.yaml` | `rl_ckpt18809_op13_20_step200_merged_hf` | 2026-08-20 12:21:26 to 14:51:54 UTC |
|
| 35 |
+
| `020305/rl/op15_20_step200` | `interplay_rl_ckpt18809_op15_20_arkeng_a100x8_r62` | `scripts/arnold/launch_rl_ckpt18809_op15_20_a100x8_arkeng_r62.yaml` | `rl_ckpt18809_op15_20_step200_merged_hf` | 2026-08-20 12:21:04 to 14:53:21 UTC |
|
| 36 |
+
| `020305/opd_refkl/op11_14_step200` | `interplay_opd_ckpt18809_teacher_op11_14_refkl_arkeng_a100x8_r75` | `scripts/arnold/launch_opd_ckpt18809_teacher_op11_14_refkl_a100x8_arkeng_r75.yaml` | `opd_ckpt18809_refkl_op11_14_s200_merged_hf` | 2026-08-22 09:28:42 to 11:59:32 UTC |
|
| 37 |
+
| `050302/pretrain/checkpoint-18586` | `interplay_fig3_pretrain_050302_arkeng_a100x8_r13` | `scripts/arnold/launch_fig3_pretrain_050302_a100x8_arkeng_r13.yaml` | `pretrain_050302_ckpt18586` | 2026-08-19 06:54:03 to 12:39:48 UTC |
|
| 38 |
+
| `050302/rl/op11_14_step200` | `interplay_rl_050302pretrain_op11_14posttrain_arkeng_a100x8_r76` | `scripts/arnold/launch_rl_050302pretrain_op11_14posttrain_a100x8_arkeng_r76.yaml` | `rl050302_op11_14_step200_merged_hf` | 2026-08-22 09:21:36 to 21:35:04 UTC |
|
| 39 |
+
| `050302/rl/op13_20_step200` | `interplay_rl_050302pretrain_op13_20posttrain_arkeng_a100x8_r76` | `scripts/arnold/launch_rl_050302pretrain_op13_20posttrain_a100x8_arkeng_r76.yaml` | `rl050302_op13_20_step200_merged_hf` | 2026-08-22 09:21:34 to 21:35:07 UTC |
|
| 40 |
+
| `050302/rl/op15_20_step200` | `interplay_rl_050302pretrain_op15_20posttrain_arkeng_a100x8_r76` | `scripts/arnold/launch_rl_050302pretrain_op15_20posttrain_a100x8_arkeng_r76.yaml` | `rl050302_op15_20_step200_merged_hf` | 2026-08-22 09:21:35 to 21:35:38 UTC |
|
| 41 |
+
| `050302/opd_refkl/op13_20_step200` | `interplay_opd_050302_teacher_op13_20_refkl_arkeng_a100x8_r80` | `scripts/arnold/launch_opd_050302_teacher_op13_20_refkl_a100x8_arkeng_r80.yaml` | `opd050302_refkl_s200_merged_hf` | 2026-08-23 22:29:00 to 2026-08-24 10:44:46 UTC |
|
| 42 |
+
|
| 43 |
+
## Evaluation Summary
|
| 44 |
+
|
| 45 |
+
All rows use 1,152,000 ID examples, 1,280,000 OOD examples, and 2,432,000 total examples.
|
| 46 |
+
|
| 47 |
+
| Model name | ID acc | OOD acc | Total acc | Evaluation artifact path |
|
| 48 |
+
| --- | ---: | ---: | ---: | --- |
|
| 49 |
+
| `pretrain_ckpt18809` | 0.362037 | 0.100438 | 0.224353 | `020305/evals/pretrain_ckpt18809/` |
|
| 50 |
+
| `rl_ckpt18809_op11_14_step200_merged_hf` | 0.800709 | 0.369602 | 0.573810 | `020305/evals/rl_ckpt18809_op11_14_step200_merged_hf/` |
|
| 51 |
+
| `rl_ckpt18809_op13_20_step200_merged_hf` | 0.683144 | 0.289346 | 0.475882 | `020305/evals/rl_ckpt18809_op13_20_step200_merged_hf/` |
|
| 52 |
+
| `rl_ckpt18809_op15_20_step200_merged_hf` | 0.388938 | 0.160735 | 0.268831 | `020305/evals/rl_ckpt18809_op15_20_step200_merged_hf/` |
|
| 53 |
+
| `opd_ckpt18809_refkl_op11_14_s200_merged_hf` | 0.801092 | 0.365645 | 0.571909 | `020305/evals/opd_ckpt18809_refkl_op11_14_s200_merged_hf/` |
|
| 54 |
+
| `pretrain_050302_ckpt18586` | 0.659137 | 0.174320 | 0.403970 | `050302/evals/pretrain_050302_ckpt18586/` |
|
| 55 |
+
| `rl050302_op11_14_step200_merged_hf` | 0.756464 | 0.348082 | 0.541526 | `050302/evals/rl050302_op11_14_step200_merged_hf/` |
|
| 56 |
+
| `rl050302_op13_20_step200_merged_hf` | 0.709700 | 0.343556 | 0.516993 | `050302/evals/rl050302_op13_20_step200_merged_hf/` |
|
| 57 |
+
| `rl050302_op15_20_step200_merged_hf` | 0.719865 | 0.291799 | 0.494567 | `050302/evals/rl050302_op15_20_step200_merged_hf/` |
|
| 58 |
+
| `opd050302_refkl_s200_merged_hf` | 0.709348 | 0.342995 | 0.516530 | `050302/evals/opd050302_refkl_s200_merged_hf/` |
|
| 59 |
+
|
| 60 |
+
## Source Pointers
|
| 61 |
+
|
| 62 |
+
- Data: <https://huggingface.co/datasets/Interplay-LM-Reasoning/composition>
|
| 63 |
+
- Context data: <https://huggingface.co/datasets/Interplay-LM-Reasoning/context>
|
| 64 |
+
- Repository documentation: `docs/extrapolation_release_wrapup.md` in the GitHub repository.
|