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Model: adilkairolla/zeta-2.1-GGUF
Source: Original Platform

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README.md

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+---
+base_model: zed-industries/zeta-2.1
+base_model_relation: quantized
+quantized_by: adilkairolla
+license: apache-2.0
+library_name: gguf
+pipeline_tag: text-generation
+tags:
+  - gguf
+  - llama.cpp
+  - quantized
+  - edit-prediction
+  - next-edit-suggestion
+  - code
+language:
+  - en
+---
+
+# Zeta 2.1 — GGUF
+
+GGUF quantizations of [`zed-industries/zeta-2.1`](https://huggingface.co/zed-industries/zeta-2.1), a code edit prediction (next-edit suggestion) model from [Zed Industries](https://zed.dev).
+
+These files were produced from the original BF16 safetensors using [llama.cpp `b9085`](https://github.com/ggml-org/llama.cpp/releases/tag/b9085) (`convert_hf_to_gguf.py` → `llama-quantize`). No fine-tuning or weight modification beyond format conversion and quantization.
+
+## Files
+
+| Quant     | Size   | Notes                                                                 |
+|-----------|-------:|-----------------------------------------------------------------------|
+| `Q4_K_M`  | 4.8 GB | Smallest, recommended default for CPU / 8 GB-class GPUs.              |
+| `Q5_K_M`  | 5.5 GB | Quality / size sweet spot.                                            |
+| `Q8_0`    | 8.2 GB | Near-lossless vs. the original BF16 weights.                          |
+| `f16`     |  16 GB | Reference. Useful as the source for further quantization.             |
+
+## Quickstart
+
+### Ollama
+
+```bash
+ollama pull hf.co/adilkairolla/zeta-2.1-GGUF:Q4_K_M
+```
+
+Replace the tag with `Q5_K_M`, `Q8_0`, or `f16` for a different quant. Zeta is a code-edit-prediction model (not a chat model) — call it via `/api/generate` with the FIM prompt below, **not** via `/api/chat`.
+
+### LM Studio
+
+Search for `adilkairolla/zeta-2.1-GGUF` in the model browser and pick a quant. LM Studio loads it as a base completion model.
+
+### llama.cpp
+
+```bash
+# One-shot completion (correct binary for non-chat models)
+./llama-completion -m zeta-2.1-Q4_K_M.gguf -p "$(cat your-prompt.txt)" -n 256 -c 4096
+```
+
+### llama-cpp-python
+
+```python
+from llama_cpp import Llama
+llm = Llama(model_path="zeta-2.1-Q4_K_M.gguf", n_ctx=4096)
+out = llm(prompt, max_tokens=256, stop=["<|marker_2|>"], echo=False)
+print(out["choices"][0]["text"])
+```
+
+## Prompt format
+
+Zeta uses a Suffix-Prefix-Middle (SPM) FIM format with numbered region markers. Quoting the upstream model card:
+
+```
+<[fim-suffix]>
+code after editable region
+<[fim-prefix]><filename>related/file.py
+related file content
+
+<filename>edit_history
+--- a/some_file.py
++++ b/some_file.py
+-old
++new
+
+<filename>path/to/target_file.py
+code before editable region
+<|marker_1|>
+code that
+needs to<|user_cursor|>
+be rewritten
+<|marker_2|>
+<[fim-middle]>
+```
+
+Expected output:
+
+```
+<|marker_1|>
+revised content for
+the editable region
+<|marker_2|>
+```
+
+See the upstream [`sample.prompt`](https://huggingface.co/zed-industries/zeta-2.1/blob/main/sample.prompt) and [`sample.output`](https://huggingface.co/zed-industries/zeta-2.1/blob/main/sample.output) for a real example.
+
+## Source & lineage
+
+- **Quantized from:** [`zed-industries/zeta-2.1`](https://huggingface.co/zed-industries/zeta-2.1) (BF16 safetensors)
+- **Fine-tuned from:** [`ByteDance-Seed/Seed-Coder-8B-Base`](https://huggingface.co/ByteDance-Seed/Seed-Coder-8B-Base)
+- **Architecture:** Llama (32 layers, hidden 4096, 32 heads, 8 KV heads, vocab 155136, RoPE θ 500000, ctx 32768)
+- **Conversion tool:** llama.cpp `b9085`
+
+## License
+
+Released under the [Apache License 2.0](https://www.apache.org/licenses/LICENSE-2.0), inherited from the upstream model. The only modification relative to upstream is the conversion to GGUF and quantization to the formats listed above.
+
+All credit for the model itself goes to Zed Industries and ByteDance-Seed. This repo is an unaffiliated quantization mirror.

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