initial upload

FINAL2_12H-best.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:bc565782b51d74fe56de1c2d9dd4e44c52b1e6ff192bfcdb758291edeaf5240c
+size 473864296

FINAL_12H-best.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:4685ab3dae35e7835ee0fdd469d23d39347b0cca0f71c0598bea30443f0d7672
+size 473864296

README.md

@@ -1,3 +1,135 @@
 ---
 license: mit
+language:
+- en
+pipeline_tag: text-generation
+tags:
+- conversational
+- dialogue
+- latent-space
+- thought-vectors
+- research
+- pytorch
 ---
+
+# thoughtvec — conversation in thought-vector space
+
+A ~48M-parameter dialogue system that never does token-level language
+modeling in its reasoning loop. Trained from scratch in ~25 GPU-hours on one
+consumer GPU (AMD RX 6700 XT, 12 GB) — a 12-hour codec run and a 12-hour
+thinker run. (That's the cost of these weights, not of the research: the
+ablation record behind them — 86 checkpointed runs — took on the order of
+another hundred GPU-hours.)
+
+It works in two parts:
+
+- A **codec** (32.9M params) turns text into a sequence of "thought vectors"
+  ordered by importance — any prefix of them decodes back to text, so
+  compression ratio is a decode-time choice. Byte-perfect at 4:1, readable
+  at 8:1.
+- A **thinker** (15.1M params) converses directly in that latent space:
+  history turns in, response thoughts out, and the frozen codec decoder
+  renders the reply. No tokens anywhere in between.
+
+```
+user > i'm feeling really overwhelmed with work lately.
+bot  > I can imagine. What's been going on?
+user > my boss keeps piling on deadlines.
+bot  > That sounds like a lot of pressure. Have you been able to talk to anyone else?
+```
+
+That transcript is greedy decoding (temperature 0), reproducible from
+`FINAL_12H-best.pt`.
+
+**Try it in the browser**: [thought-vectors-chat](https://huggingface.co/spaces/nochinator/thought-vectors-chat)
+
+## What to expect — and not
+
+This is a research model, and a small one. It holds coherent, grounded,
+context-sensitive small talk: openings, follow-up questions, multi-turn
+reference. That is the finding — conversational competence at this level
+does not require a token-level LM in the loop.
+
+It is *not* a general assistant. No knowledge tasks, English small talk
+only. And it has one well-documented disease: it can reply cheerfully to
+bad news, especially after an upbeat turn ("That's good to hear." to
+insomnia). The paper traces that failure through three ablation rounds to
+a training-data absence — no conversation in any corpus used ever reverses
+mood mid-dialogue — and shows that even targeted data patching bought only
+partial, topic-gated routing rather than the skill (the patched case-study
+model commiserates with illness or job loss, and still cheers a burglary
+or a hailstorm). If you probe the model, you will find it; it's a case
+study, not a surprise.
+
+## Files
+
+| File | What it is |
+|---|---|
+| `FINAL_12H-best.pt` | Thinker flagship (use this one to chat) |
+| `FINAL2_12H-best.pt` | Register case-study run (+EmpatheticDialogues +reversal splices) |
+| `m5_frontier-best.pt` | Codec — needed alongside either thinker |
+| `spm16k_bpe.model` | 16K SentencePiece tokenizer — all checkpoints depend on it |
+
+SHA-256 (byte-identical to the [GitHub Release](https://github.com/nochinator/thought-vectors/releases/tag/v1.1.0) assets):
+
+```
+4685ab3dae35e7835ee0fdd469d23d39347b0cca0f71c0598bea30443f0d7672  FINAL_12H-best.pt
+bc565782b51d74fe56de1c2d9dd4e44c52b1e6ff192bfcdb758291edeaf5240c  FINAL2_12H-best.pt
+77bf080cc216f628fa80c260acc2cfe2ffb03c19bc3d44071047ad4377b0e4ad  m5_frontier-best.pt
+```
+
+The paper's matched token-LM baseline (`b3_lm_48m_24h-best.pt`, §6.5) ships
+as a GitHub Release asset only — it is the comparison model, not part of
+this system.
+
+## Run it locally
+
+CPU is enough — chat inference runs on CPU by design.
+
+```bash
+git clone https://github.com/nochinator/thought-vectors
+cd thought-vectors
+scripts/setup_env.sh --cpu
+
+# place the files (thinker embeds codec weights but reads codec config
+# from the codec file — you need both):
+#   FINAL_12H-best.pt   -> checkpoints/FINAL_12H/best.pt
+#   m5_frontier-best.pt -> checkpoints/m5_frontier/best.pt
+
+.venv/bin/tv-chat --ckpt checkpoints/FINAL_12H/best.pt --device cpu
+```
+
+## Results at a glance
+
+| Run | val_cos ↑ | ref_F1 ↑ | self_rep ↓ | ctx_sens ↓ |
+|---|---|---|---|---|
+| FINAL_12H (flagship) | **0.428** | **0.297** | 0.188 | **0.146** |
+| FINAL2_12H (case study) | 0.415 | 0.278 | **0.154** | 0.206 |
+
+Codec: byte-perfect reconstruction at 4:1 compression through 257 tokens;
+graceful degradation at 8:1 and beyond. Every number maps to a named log
+file in the repo — the full experimental record, including the negative
+rounds and four incidents of models gaming lexical metrics, is in
+[RESEARCH_LOG.md](https://github.com/nochinator/thought-vectors/blob/main/RESEARCH_LOG.md).
+
+## Links
+
+- **Paper**: [DOI 10.5281/zenodo.21262842](https://doi.org/10.5281/zenodo.21262842) — also as
+  [PDF in the repo](https://github.com/nochinator/thought-vectors/blob/main/paper/main.pdf)
+- **Code + logs**: https://github.com/nochinator/thought-vectors
+- **Reproduce from scratch** (~25 GPU-hours, one RX 6700 XT):
+  [docs/REPRODUCE.md](https://github.com/nochinator/thought-vectors/blob/main/docs/REPRODUCE.md)
+
+## Citation
+
+```bibtex
+@misc{nochi2026thoughtvectors,
+  author = {nochi},
+  title  = {Codecs: Separating Meaning from Language --- Coherent
+            Dialogue in Thought-Vector Space from 48M Parameters on One
+            Consumer GPU},
+  year   = {2026},
+  doi    = {10.5281/zenodo.21262842},
+  url    = {https://github.com/nochinator/thought-vectors}
+}
+```

m5_frontier-best.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:77bf080cc216f628fa80c260acc2cfe2ffb03c19bc3d44071047ad4377b0e4ad
+size 394192405

spm16k_bpe.model

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:1207edb30a54266ef361f6146e56c8f1c4e16fb28ac525f9895adc0e76e10bdd
+size 503814