docs: v0.55 — wiki warmup complete, checkpoint deprecation notice

README.md

@@ -21,17 +21,28 @@ Non-transformer architecture. No attention mechanism. Constitutional training vi
 
 ---
 
-## What's in this repo
+## ⚠️ Checkpoint Deprecation Notice
+
+| Checkpoint | Status | Notes |
+|---|---|---|
+| `Anvaya-Rabbit-2.7B-0.55-base.pt` | ✅ **CURRENT** | Wikipedia warmup complete, CE 0.993x |
+| Any prior checkpoint | ⚠️ **DEPRECATED** | Do not use for inference |
+
+Prior checkpoints are retained for research transparency.  
+The current checkpoint reflects iterative refinement of the  
+ANVAYA RtaSSM architecture and training pipeline.
+
+**Always use the latest `-base.pt` for any downstream work.**
 
-Three model tiers are available, each built on the same 2.7B parameter base:
+---
+
+## What's in this repo
 
 | Tier | File | Use this when… |
 |---|---|---|
-| **Base** | `base/Anvaya-Rabbit-2.7B-0.5-alpha-base.pt` | You want raw pretrained weights for your own fine-tuning |
-| **Instruct** | `instruct/Anvaya-Rabbit-2.7B-0.5-alpha-instruct.pt` | You want a general-purpose assistant that follows instructions |
-| **Imprint** | `imprint/Anvaya-Rabbit-2.7B-0.5-alpha-imprint.pt` | You want the full Rabbit persona — opinionated, constitutional, identity-aware |
+| **Base** | `base/Anvaya-Rabbit-2.7B-0.55-base.pt` | You want raw pretrained weights for your own fine-tuning |
 
-If you're not sure which to use, start with **Instruct**.
+Instruct and Imprint tiers are in preparation (epoch 2 → SFT → imprint pipeline).
 
 ---
 
@@ -54,15 +65,12 @@ model = AutoModelForCausalLM.from_pretrained(
     device_map="auto",
 )
 
-# v0.5-alpha uses raw completion format
 prompt = "Rabbit is a helpful and honest assistant.\n\nUser: Who are you?\nRabbit:"
 inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
 outputs = model.generate(**inputs, max_new_tokens=60, repetition_penalty=1.3)
 print(tokenizer.decode(outputs[0], skip_special_tokens=True))
 ```
 
-> *v0.5-alpha uses raw completion format. Chat template support (ChatML) coming in v0.9.*
-
 > The `rtaforge` runtime package provides the compiled architecture. Source is not distributed.
 
 ---
@@ -88,9 +96,10 @@ Rabbit is built on **RtaSSM v7.2.2-FU "Fortress Unbroken"**, a custom state-spac
 
 | Stage | Data | Notes |
 |---|---|---|
-| Wiki pretraining | Wikipedia (en) | 732 constitutional proposals via Gurukul |
-| Instruct SFT | ChatML instruction pairs | `gate_only` trainable strategy |
-| Persona imprint | Rabbit constitutional corpus | Identity and value alignment |
+| Wiki warmup (v0.55) | Wikipedia (en) | 700 constitutional proposals via Gurukul — **complete** |
+| Epoch 2 (planned) | RedPajama | Gate-only, ~3,350 proposals |
+| Instruct SFT (planned) | ChatML instruction pairs | `gate_only` trainable strategy |
+| Persona imprint (planned) | Rabbit constitutional corpus | Identity and value alignment |
 
 ---
 
@@ -112,16 +121,15 @@ Runtime documentation coming soon.
 
 ## Maturity and Roadmap
 
-**v0.5-alpha is a proof of concept.** It demonstrates that the RtaSSM architecture trains end-to-end, the Gurukul constitutional pipeline works, and the weights are real.
-
+**v0.55 is a base pretrained checkpoint** — Wikipedia warmup complete, CE ratio 0.993×.  
 Usable conversational behaviour is targeted at **v0.8–v0.9**, currently in training.
 
 - Evaluating for deployment? Wait for v0.9.
-- Evaluating the architecture or training methodology? v0.5-alpha is exactly what you need.
+- Evaluating the architecture or training methodology? v0.55-base is exactly what you need.
 
 ## Limitations
 
-v0.5-alpha has not been evaluated on standard benchmarks. She is small, she is new, and she is learning. Feedback welcome at guha@rtaforge.in.
+v0.55 has not been evaluated on standard benchmarks. She is small, she is new, and she is learning. Feedback welcome at guha@rtaforge.in.
 
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