Instructions to use SceneWorks/hemispheres-step1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use SceneWorks/hemispheres-step1 with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download SceneWorks/hemispheres-step1 --local-dir hemispheres-step1
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
Upload context-a, context-multi-bios, context-multi-bios-20k, context-multi-bios-20k-s1, dense-a, dense-a-k100, dense-a-to-b, latent-a, latent-a-all, latent-multi, latent-multi-nohop, lookup-a
790f3b4 verified Download context-multi-bios/config.json from SceneWorks/hemispheres-step1: direct link, hf CLI and curl.
- Browser
- Download file 2.98 kB
-
https://huggingface.co/SceneWorks/hemispheres-step1/resolve/main/context-multi-bios/config.json
- Command line
-
hf download hf://SceneWorks/hemispheres-step1/context-multi-bios/config.json
-
curl -L -o config.json https://huggingface.co/SceneWorks/hemispheres-step1/resolve/main/context-multi-bios/config.json
2.98 kB
| { | |
| "arm": "context", | |
| "data": "data/world-a,data/pool/w3-s0,data/pool/w3-s1,data/pool/w3-s2,data/pool/w4-s0,data/pool/w4-s1,data/pool/w4-s2,data/pool/w5-s0,data/pool/w5-s1,data/pool/w5-s2,data/pool/w6-s0,data/pool/w6-s1,data/pool/w6-s2,data/pool/w7-s0,data/pool/w7-s1,data/pool/w7-s2", | |
| "out": "runs/context-multi-bios", | |
| "edits": 0, | |
| "mix": [ | |
| [ | |
| "bios", | |
| 0.5 | |
| ], | |
| [ | |
| "qa", | |
| 0.5 | |
| ] | |
| ], | |
| "init": null, | |
| "init_checkpoint": "final", | |
| "size": "small", | |
| "dtype": "float32", | |
| "steps": 10000, | |
| "batch_size": 64, | |
| "seq_len": 256, | |
| "lr": 0.001, | |
| "min_lr_frac": 0.1, | |
| "warmup": 500, | |
| "weight_decay": 0.1, | |
| "grad_clip": 1.0, | |
| "log_every": 100, | |
| "eval_every": 2000, | |
| "eval_sets": "test_id,test_ood,test_1hop_ood", | |
| "eval_n": 200, | |
| "save_every": 2000, | |
| "seed": 0, | |
| "n_reads": 3, | |
| "top_k": 4, | |
| "hop_weight": 0.5, | |
| "hop_until": 0, | |
| "max_supervision": 1024, | |
| "supervise": "all", | |
| "model_type": "gpt", | |
| "model": { | |
| "vocab_size": 576, | |
| "n_layer": 8, | |
| "n_head": 8, | |
| "d_model": 512, | |
| "mlp_ratio": 4, | |
| "rope_base": 10000.0 | |
| }, | |
| "params": 25469440, | |
| "vocab": 544, | |
| "provenance": { | |
| "time": "2026-09-25T17:18:09+00:00", | |
| "code": { | |
| "commit": "4fc4e676ef82fd2bb4ea3bddc5f4471bc12f3e93", | |
| "dirty": false | |
| }, | |
| "env": { | |
| "python": "3.12.11", | |
| "platform": "macOS-26.6.2-arm64-arm-64bit", | |
| "machine": "arm64", | |
| "mlx": "0.32.2", | |
| "device": "Device(gpu, 0)" | |
| }, | |
| "data": { | |
| "data/world-a": "befab6f0a218e36f48e7ae53539eef4e3fe9fab49eaae9a2d603ee01b86df106", | |
| "data/pool/w3-s0": "0ba111647c1a6a792997fc6d120b87af91c5bd74a980e6f82dc486138f43dfb5", | |
| "data/pool/w3-s1": "d17f343e6096fb6f8458fcffe773f86584f795f84710887f822f1a99dc1c1599", | |
| "data/pool/w3-s2": "a6bfacf6b64cf3a7593eb72eb54a1f7c1467a50a302e4145f0d09317a3e99220", | |
| "data/pool/w4-s0": "45133b232f854baca586b26947f3e8c5466131936e361fccf164caecd0af2b57", | |
| "data/pool/w4-s1": "baf14fe23044cc3bb44a06592f7c97dbe7c3841a1b8a4fb8520d142230070786", | |
| "data/pool/w4-s2": "fefdd4a7b1d055d3075ee7f381a654fc409676648e987dd5cdc6c81ee4419131", | |
| "data/pool/w5-s0": "467ceab0c667d7fc25a1c46aa6c32a93bc7fe73b9ee772dd418d5cd39c06578a", | |
| "data/pool/w5-s1": "ec9eff474e21c22c230e4751a853ba5aabd701dcc3954ed01d1ff6343d49d95b", | |
| "data/pool/w5-s2": "961b61d99794256fda9268f30e77f88e6b62f3bac930536344bd655c3570bff1", | |
| "data/pool/w6-s0": "0be7dec6c651b282845efbc7a52315ef85919828726e8d6265d9a2daee95e782", | |
| "data/pool/w6-s1": "c923a29d763af2a7e9b7de4fa884c175ac5ca8b9da380187d5df98c3de0b77d6", | |
| "data/pool/w6-s2": "3a9229340fd51a3ccce5bff9757ce996ff778bd75e8268a0008be8f333ddfa6e", | |
| "data/pool/w7-s0": "d9f42180c24d99f7c7489d4e785b816aed0db787ace2995044e8b26799594eee", | |
| "data/pool/w7-s1": "66e4ce0a96656931b70e219b20938fd899f821399bc320e2fd3a8933189e7d6b", | |
| "data/pool/w7-s2": "59655904ea2784b39a94561b1ef60d2b7d4012a9089ddf8e6f63b8a38184ec2d" | |
| } | |
| } | |
| } |