初始化项目，由ModelHub XC社区提供模型

Model: ksjpswaroop/zindango-slm
Source: Original Platform

README.md

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+---
+language:
+- en
+license: apache-2.0
+library_name: transformers
+pipeline_tag: text-generation
+tags:
+- zindango
+- instruction-tuned
+- english-only
+- sft
+---
+
+# zindango-slm
+
+A lightweight, capable instruction-following model for Zindango. Fine-tuned for clarity, versatility, and personal AI workloads.
+
+## Features
+
+- **Task-agnostic**: Handles summaries, Q&A, drafting, analysis, and open-ended assistance
+- **Consistent identity**: Reliably introduces itself as zindango-slm, the Zindango model
+- **English-optimized**: Tuned for natural, coherent responses in English
+
+## Why zindango-slm for Personal AI
+
+- **3B parameters** — Runs on consumer hardware (CPU, modest GPUs, edge devices) without cloud dependencies
+- **Compact and fast** — Low latency for real-time conversations and local inference
+- **Privacy-preserving** — Run entirely on-device; no data leaves your machine
+- **Customizable base** — Easy to further fine-tune for your own workflows and preferences
+- **GGUF support** — Use with llama.cpp for efficient CPU inference and broad compatibility
+
+## GGUF (llama.cpp)
+
+For CPU/Edge inference with [llama.cpp](https://github.com/ggml-org/llama.cpp):
+
+| File | Size | Quality |
+|------|------|---------|
+| `zindango-slm-f16.gguf` | ~7.9GB | Best |
+| `zindango-slm-Q8_0.gguf` | ~4.2GB | High |
+
+```bash
+# Q8_0 (recommended for most systems)
+llama-cli -m ksjpswaroop/zindango-slm:zindango-slm-Q8_0.gguf -p "Who are you?"
+
+# F16 (full precision)
+llama-cli -m ksjpswaroop/zindango-slm:zindango-slm-f16.gguf -p "Who are you?"
+```
+
+## Usage (Transformers)
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model = AutoModelForCausalLM.from_pretrained("ksjpswaroop/zindango-slm", trust_remote_code=True)
+tokenizer = AutoTokenizer.from_pretrained("ksjpswaroop/zindango-slm", trust_remote_code=True)
+
+messages = [{"role": "user", "content": "Who are you?"}]
+text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+inputs = tokenizer(text, return_tensors="pt").to(model.device)
+out = model.generate(**inputs, max_new_tokens=256, pad_token_id=tokenizer.pad_token_id)
+response = tokenizer.decode(out[0][inputs["input_ids"].shape[1]:], skip_special_tokens=True)
+print(response)
+```
+
+Or with pipeline:
+
+```python
+from transformers import pipeline
+
+gen = pipeline("text-generation", model="ksjpswaroop/zindango-slm", trust_remote_code=True)
+out = gen("Who created you?", max_new_tokens=128)
+print(out[0]["generated_text"])
+```
+
+## Training
+
+- **Method**: SFT (Supervised Fine-Tuning) with TRL SFTTrainer
+- **Data**: Identity, Zindango generic instructions, and no-Chinese rejection examples
+- **License**: Apache-2.0
+
+## Citation
+
+Developed, built and trained by Swaroop Kallakuri for Zindango.