Add model card

README.md

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+---
+license: llama3
+language:
+- sv
+- da
+- "no"
+- en
+base_model: AI-Sweden-Models/Llama-3-8B-instruct
+base_model_relation: quantized
+library_name: exllamav2
+tags:
+- exl2
+- llama
+- swedish
+- quantized
+---
+
+# AI-Sweden Llama-3-8B-instruct — EXL2
+
+ExLlamaV2 / EXL2 quants of [AI-Sweden-Models/Llama-3-8B-instruct](https://huggingface.co/AI-Sweden-Models/Llama-3-8B-instruct).  
+That checkpoint is a Swedish/Nordic instruct tune of Llama 3 8B. Official Hub files are BF16 (and a separate GGUF); there were no EXL2 uploads.
+
+Converted with **ExLlamaV2 0.3.2**, `lm_head` at 6-bit, **built-in default calibration** (same recipe as turboderp-style quants). One measurement pass, then each bitrate from `measurement.json`.
+
+## Branches
+
+| Revision | Target bpw | Size (approx.) |
+|---|---|---|
+| [`4.0bpw`](../../tree/4.0bpw) | 4.0 | 4.7 GB |
+| [`4.5bpw`](../../tree/4.5bpw) | 4.5 | 5.1 GB |
+| [`5.0bpw`](../../tree/5.0bpw) | 5.0 | 5.5 GB |
+| [`5.5bpw`](../../tree/5.5bpw) | 5.5 | 5.9 GB |
+| [`6.0bpw`](../../tree/6.0bpw) | 6.0 | 6.3 GB |
+
+[`measurement.json`](../../blob/main/measurement.json) is on `main` if you want to roll another bitrate yourself.
+
+Download a revision:
+
+```bash
+hf download oxfrug/Llama-3-8B-instruct-exl2 --revision 5.0bpw --local-dir ./Llama-3-8B-instruct-exl2-5.0bpw
+```
+
+TabbyAPI / ExUI: point the model path at a checked-out branch, or set the HF revision to `5.0bpw`.
+
+## Notes
+
+- **License:** [Meta Llama 3 Community License](https://llama.meta.com/llama3/license). Keep the `NOTICE` file. This is a derivative of Meta Llama 3 via AI Sweden’s instruct tune.
+- **Loader:** ExLlamaV2 (TabbyAPI, text-generation-webui `exllamav2`, ExUI). Not GGUF / llama.cpp.
+- On **PyTorch 2.13** without Flash Attention 2.5.7+, set `config.no_sdpa = True` before load. Default SDPA + `causal_lower_right` produced collapsed output in our tests; the explicit matmul path matched BF16 (6.0bpw raw-EN first 16 tokens identical). Older torch + flash-attn (paged attention) is the usual community stack and was not the convert path.
+- These are **not** the experimental Swedish-heavy calibration files. Default EXL2 cal is what other EXL2 repos ship.
+
+## Source
+
+```
+AI-Sweden-Models/Llama-3-8B-instruct
+  ← AI-Sweden-Models/Llama-3-8B
+    ← meta-llama/Meta-Llama-3-8B
+```
+
+Convert: ExLlamaV2 `convert.py` 0.3.2, RTX 3090.
+
+## Smoke (greedy, `no_sdpa=True`)
+
+6.0bpw, same chat template as the BF16 card:
+
+| Prompt | Output |
+|---|---|
+| `Vad heter Sveriges huvudstad? Ett ord.` | `Huvudstaden i Sverige är Stockholm.` |
+| `Name the capital of Sweden in one word.` | `Stockholm` |
+
+4.0bpw is coherent on the same prompts (Swedish-first on the English question, like the BF16 base). This is not a leaderboard score.