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Model: Miki-T/JARVIS-Mistral-Phase1b-GGUF Source: Original Platform
2026-08-11 03:05:16 +08:00
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+---
+base_model: mistralai/Mistral-7B-v0.1
+library_name: gguf
+pipeline_tag: text-generation
+tags:
+  - gguf
+  - mistral
+  - macedonian
+  - llama-cpp
+license: mit
+language:
+  - mk
+---
+
+# JARVIS-Mistral-Phase1b-GGUF
+
+**Model ID:** `Miki-T/JARVIS-Mistral-Phase1b-GGUF`
+
+GGUF-format versions of the JARVIS Mistral 7B Phase 1b model for use with llama.cpp and llama-cpp-python. This is the inference-ready deployment format of `Miki-T/JARVIS-Mistral-Phase1b`.
+
+---
+
+## Files
+
+| File | Size | Description |
+|------|------|-------------|
+| `mistral-7b-jarvis-phase1b.Q4_K_M.gguf` | 4.1GB | 4-bit quantized — recommended for daily use |
+| `mistral-7b-jarvis-phase1b.f16.gguf` | 14.5GB | Full float16 — master file for requantization |
+
+---
+
+## Model Details
+
+This model is the result of merging two LoRA adapters into base Mistral 7B:
+
+- **Phase 1a adapter** (`Miki-T/JARVIS-Mistral-Phase1a`) — Macedonian language foundation trained on 500k rows of Macedonian web text
+- **Phase 1b adapter** (`Miki-T/JARVIS-Mistral-Phase1b`) — Macedonian instruction following trained on 134k instruction-response pairs
+
+The adapters were merged sequentially using `merge_and_unload()`, converted to GGUF via `convert_hf_to_gguf.py`, and quantized to Q4_K_M via `llama-quantize`.
+
+| Property | Value |
+|----------|-------|
+| Base model | mistralai/Mistral-7B-v0.1 |
+| Language | Macedonian (mk), English (en) |
+| Format | GGUF |
+| Quantization | Q4_K_M (recommended), f16 (master) |
+| Context length | 32768 tokens |
+
+---
+
+## Usage
+
+### With llama-cpp-python
+
+```python
+from llama_cpp import Llama
+
+model = Llama(
+    model_path="mistral-7b-jarvis-phase1b.Q4_K_M.gguf",
+    n_ctx=2048,
+    n_gpu_layers=40,
+    verbose=False,
+)
+
+prompt = "[INST] Кој е главен град на Македонија? [/INST]"
+response = model(prompt, max_tokens=256, temperature=0.7)
+print(response["choices"][0]["text"])
+# Output: Скопје е главниот град на Македонија.
+```
+
+### Prompt format
+
+Uses Mistral instruct format:
+[INST] <<SYS>>
+Your system prompt here
+<</SYS>>
+User message [/INST] Assistant response
+
+---
+
+## Hardware
+
+- **Trained on:** NVIDIA RTX 5070 (12GB VRAM)
+- **Q4_K_M inference:** ~4.1GB VRAM, runs on any GPU with 6GB+
+- **f16 inference:** ~14.5GB VRAM
+
+---
+
+## Merge and Conversion
+
+```python
+# Step 1 — Merge adapters
+from transformers import AutoModelForCausalLM
+from peft import PeftModel
+import torch
+
+model = AutoModelForCausalLM.from_pretrained(
+    "mistralai/Mistral-7B-v0.1",
+    torch_dtype=torch.float16,
+    device_map="cpu",
+)
+model = PeftModel.from_pretrained(model, "path/to/phase1a/adapter")
+model = model.merge_and_unload()
+model = PeftModel.from_pretrained(model, "path/to/phase1b/adapter")
+model = model.merge_and_unload()
+model.save_pretrained("merged_model/")
+
+# Step 2 — Convert to GGUF (requires llama.cpp)
+# python convert_hf_to_gguf.py merged_model/ --outfile model.f16.gguf --outtype f16
+
+# Step 3 — Quantize
+# llama-quantize.exe model.f16.gguf model.Q4_K_M.gguf Q4_K_M
+```
+
+---
+
+## Related Repositories
+
+- **Phase 1a adapter:** `Miki-T/JARVIS-Mistral-Phase1a`
+- **Phase 1b adapter:** `Miki-T/JARVIS-Mistral-Phase1b`
+- **Project:** https://github.com/MikiTrajkovski/JARVIS
+
+---
+
+## License
+
+MIT License
+
+---
+
+**Author:** Miki Trajkovski | [GitHub](https://github.com/MikiTrajkovski/JARVIS) | [HuggingFace](https://huggingface.co/Miki-T)
+
+**Last Updated:** July 3, 2026
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