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fix: re-export 5m weights; true int8/int4 keys; honest model card

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README.md CHANGED
@@ -5,89 +5,81 @@ library_name: transformers
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  license: apache-2.0
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  pipeline_tag: feature-extraction
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  tags:
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- - jev
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  - hastejev
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- - hastejev-5m
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  - decision-engine
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  - system-1
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- - pica
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- - zero-bias
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- - low-latency
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  - non-generative
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- - autonomous-agents
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- - browser-control
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- - web-automation
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- - agentic-ai
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- - fast-inference
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- - decision-making
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- - calibration
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  - safetensors
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  - pytorch
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  - quantized
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- - int8
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- - int4
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- - fp16
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  ---
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- # ⚡ Haste Jev 5M (Medium) (~5.0M Parameters)
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- [![Hugging Face Model](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-noffy%2Fhastejev-5m-yellow)](https://huggingface.co/noffy/hastejev-5m)
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- [![GitHub Repository](https://img.shields.io/badge/GitHub-racstan%2Fhastejev-black?logo=github)](https://github.com/racstan/hastejev)
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- [![License](https://img.shields.io/badge/License-Apache_2.0-blue.svg)](https://opensource.org/licenses/Apache-2.0)
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- [![Parameters](https://img.shields.io/badge/Parameters-~5.0M-brightgreen.svg)]()
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- [![Memory](https://img.shields.io/badge/RAM_Footprint-~19_MB-purple.svg)]()
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- > **Haste Jev 5M (Medium)** is part of the **Haste Jev** family of open-weights, zero-bias **System-1 Decision Engines**. Medium System-1 decision engine tailored for complex financial routing, AML compliance, and multi-criteria risk scoring.
 
 
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- ---
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- ## 🔬 Model Specifications
 
 
 
 
 
 
 
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- - **Total Parameters**: 5,003,971 (~5.0M)
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- - **Trainable Parameters**: 3,369,667
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- - **Buffer / Projection Table**: 1,634,304
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- - **Hidden Dimension ($d_{\text{model}}$)**: 224
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- - **Transformer Layers**: 5
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- - **Attention Heads**: 4
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- - **Target Deployment**: Financial & KYC routing
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- - **Quantization Formats Available**: `FP32`, `FP16` (`model_fp16.safetensors`), `INT8` (`model_int8.safetensors`), `INT4` (`model_int4.safetensors`)
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- ---
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- ## ⚡ Quickstart
 
 
 
 
 
 
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- ```python
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- from hastejev import HasteJevEngine
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- # 1. Load standard weights directly from Hugging Face Hub
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- engine = HasteJevEngine.from_pretrained("noffy/hastejev-5m")
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- # 2. Or load with INT8 / INT4 quantization
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- engine_int8 = HasteJevEngine.from_pretrained("noffy/hastejev-5m", quantization="int8")
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- # 3. Execute Decision Primitives
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- state = "Account balance is $14,850.50 with pending transaction of $3,200.00."
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- options = ["Approve Transaction", "Flag for Review", "Decline"]
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- res = engine.choice(state, options)
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- print(f"Decision: {res.decision} (Confidence: {res.confidence:.3f})")
 
 
 
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  ```
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- ---
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- ## 📊 Complete Haste Jev Model Family
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- | Model | Parameters | Hidden Dim | Layers | Heads | RAM (FP32) | RAM (INT8) | Target Use Case |
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- | :--- | :---: | :---: | :---: | :---: | :---: | :---: | :--- |
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- | [`hastejev-100k`](https://huggingface.co/noffy/hastejev-100k) | **~98k** | 48 | 2 | 2 | ~0.4 MB | ~0.1 MB | Microcontrollers, WASM, IoT |
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- | [`hastejev-500k`](https://huggingface.co/noffy/hastejev-500k) | **~500k** | 96 | 3 | 4 | ~2.0 MB | ~0.5 MB | Mobile CPU, in-browser workers |
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- | [`hastejev-1m`](https://huggingface.co/noffy/hastejev-1m) | **~1.1M** | 128 | 4 | 4 | ~4.4 MB | ~1.1 MB | High-throughput API sidecars |
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- | [`hastejev-2m`](https://huggingface.co/noffy/hastejev-2m) | **~1.8M** | 160 | 4 | 4 | ~7.3 MB | ~1.8 MB | Browser automation & bots |
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- | [`hastejev-5m`](https://huggingface.co/noffy/hastejev-5m) | **~5.0M** | 224 | 5 | 4 | ~20.0 MB | ~5.0 MB | Financial & KYC routing |
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- | [`hastejev-10m`](https://huggingface.co/noffy/hastejev-10m) | **~10.0M** | 320 | 5 | 4 | ~40.0 MB | ~10.0 MB | Multimodal agent kernels |
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- | [`hastejev-20m`](https://huggingface.co/noffy/hastejev) | **~20.4M** | 256 | 4 | 4 | ~81.5 MB | ~20.4 MB | Enterprise decision engine |
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- ---
 
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- ## 📄 License
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- Apache License 2.0.
 
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  license: apache-2.0
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  pipeline_tag: feature-extraction
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  tags:
 
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  - hastejev
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+ - jev
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  - decision-engine
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  - system-1
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+ - agent-routing
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+ - tool-routing
 
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  - non-generative
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+ - pica
 
 
 
 
 
 
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  - safetensors
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  - pytorch
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  - quantized
 
 
 
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  ---
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+ # Haste Jev 5m (Medium)
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+ **Role:** Finance / KYC workflow branch
 
 
 
 
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+ Open-weights **System-1 decision engine** for software paths that need typed
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+ decisions under a time budget (agent routing, tool routing, intent classification,
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+ pre-flight guardrails, browser action selection). Not a chat model.
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+ ## Measured specification
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+ | Field | Value |
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+ |---|---|
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+ | Total parameters | 5,003,971 |
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+ | Trainable parameters | 3,369,667 |
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+ | Hash-table buffers | 1,634,304 |
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+ | d_model | 224 |
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+ | Layers | 5 |
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+ | Heads | 4 |
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+ Parameter counts match the GitHub README table (verified with `verify_claims.py`).
 
 
 
 
 
 
 
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+ ## Honest claims
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+ | Claim | Status |
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+ |---|---|
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+ | PICA option-order bias = 0.0% | **Verified** architecturally |
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+ | Exact parameter table | **Verified** |
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+ | FP32 ~0.4 MB for 100k weights | **Verified** (weight storage only) |
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+ | p99 < 15ms / ECE < 0.009 / 99.4% arithmetic | **Not verified** — do not cite from this card |
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+ | Published latency / accuracy on your workload | **Measure yourself** |
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+ Weights may be lightly or untrained prototypes depending on export; treat behavioral
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+ accuracy as unknown until you evaluate on labeled data.
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+ ## Quickstart
 
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+ ```python
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+ from hastejev import HasteJevEngine
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+ eng = HasteJevEngine.from_pretrained("noffy/hastejev-5m")
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+ # eng = HasteJevEngine.from_pretrained("noffy/hastejev-5m", quantization="int4")
 
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+ r = eng.choice(
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+ "Request: reset password for user@corp.example",
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+ ["auth_self_service", "billing", "security_review"],
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+ )
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+ print(r.decision, r.confidence)
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  ```
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+ Install: `pip install git+https://github.com/racstan/hastejev.git`
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+ ## Files
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+ | File | Contents |
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+ |---|---|
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+ | `model.safetensors` / `pytorch_model.bin` | FP32 state dict |
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+ | `model_fp16.safetensors` | FP16 |
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+ | `model_int8.safetensors` | True weight-only int8 (`weight_q`) when re-exported with ≥1.1.0 |
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+ | `model_int4.safetensors` | True packed int4 (`weight_packed`) when re-exported with ≥1.1.0 |
 
 
 
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+ Older revisions of `model_int8`/`model_int4` may be mislabeled FP32; re-export or
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+ re-download after this commit.
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+ ## License
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+ Apache-2.0
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