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zed-industries/zeta-2.1, a code edit prediction (next-edit suggestion) model from Zed Industries.b9085 (convert_hf_to_gguf.py → llama-quantize). No fine-tuning or weight modification beyond format conversion and quantization.| 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. |
ollama pull hf.co/adilkairolla/zeta-2.1-GGUF:Q4_K_MQ5_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.adilkairolla/zeta-2.1-GGUF in the model browser and pick a quant. LM Studio loads it as a base completion model.1# One-shot completion (correct binary for non-chat models)
2./llama-completion -m zeta-2.1-Q4_K_M.gguf -p "$(cat your-prompt.txt)" -n 256 -c 40961from llama_cpp import Llama
2llm = Llama(model_path="zeta-2.1-Q4_K_M.gguf", n_ctx=4096)
3out = llm(prompt, max_tokens=256, stop=["<|marker_2|>"], echo=False)
4print(out["choices"][0]["text"])<[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]><|marker_1|>
revised content for
the editable region
<|marker_2|>sample.prompt and sample.output for a real example.zed-industries/zeta-2.1 (BF16 safetensors)ByteDance-Seed/Seed-Coder-8B-Baseb9085