初始化项目，由ModelHub XC社区提供模型

Model: kulia-moon/Lily-Qwen1.5-0.5B
Source: Original Platform

.gitattributes

@@ -0,0 +1,36 @@
+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ckpt filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.mlmodel filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.npy filter=lfs diff=lfs merge=lfs -text
+*.npz filter=lfs diff=lfs merge=lfs -text
+*.onnx filter=lfs diff=lfs merge=lfs -text
+*.ot filter=lfs diff=lfs merge=lfs -text
+*.parquet filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pickle filter=lfs diff=lfs merge=lfs -text
+*.pkl filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+*.safetensors filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tar filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
+*.tgz filter=lfs diff=lfs merge=lfs -text
+*.wasm filter=lfs diff=lfs merge=lfs -text
+*.xz filter=lfs diff=lfs merge=lfs -text
+*.zip filter=lfs diff=lfs merge=lfs -text
+*.zst filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,183 @@
+---
+library_name: transformers
+license: mit
+language:
+- en
+- zh
+base_model:
+- Qwen/Qwen1.5-0.5B
+- Qwen/Qwen1.5-0.5B-Chat
+datasets:
+- Abirate/english_quotes
+---
+![Banner](https://image.pollinations.ai/prompt/Garden%20hub%2C%20anime%20text%20%22Lily-Qwen1.5-0.5B%22%20with%20anime%20girl%20love%20flowers?height=576&seed=9466&nologo=true&model=flux#ref)
+
+# Lily-Qwen1.5-0.5B
+
+**Lily-Qwen1.5-0.5B** is a fine-tuned version of the Qwen1.5-0.5B model, optimized for enhanced performance in natural language processing tasks. Built on the Transformer architecture with SwiGLU activation, attention QKV bias, and group query attention, it offers improved multilingual support and stable handling of up to 32K context length. This model excels in text generation, conversational dialogue, and language understanding, making it ideal for chatbots, content creation, and interactive applications.
+
+## Installation
+
+Ensure you have the required dependencies installed:
+
+```bash
+pip install transformers>=4.37.0 torch
+```
+
+## Usage Examples
+
+### 1. Loading the Model and Tokenizer
+
+Load the model and tokenizer using the Hugging Face `transformers` library:
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+# Load model and tokenizer
+model = AutoModelForCausalLM.from_pretrained("kulia-moon/Lily-Qwen1.5-0.5B", torch_dtype="auto", device_map="auto")
+tokenizer = AutoTokenizer.from_pretrained("kulia-moon/Lily-Qwen1.5-0.5B")
+```
+
+### 2. Generating Text with a Prompt
+
+Generate text based on a simple prompt:
+
+```python
+# Define prompt
+prompt = "Write a short story about a magical garden."
+
+# Create chat template
+messages = [
+    {"role": "system", "content": "You are a creative assistant with a passion for storytelling."},
+    {"role": "user", "content": prompt}
+]
+
+# Apply chat template
+text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+
+# Tokenize input
+model_inputs = tokenizer([text], return_tensors="pt")
+
+# Generate response
+generated_ids = model.generate(model_inputs.input_ids, max_new_tokens=512)
+
+# Decode output
+response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
+print(response)
+```
+
+**Expected Output** (example):
+> In a hidden valley, there bloomed a magical garden where flowers sang softly under the moonlight. Lily, a young explorer, stumbled upon it one evening...
+
+### 3. Engaging in Conversational Dialogue
+
+Use the model for interactive chat:
+
+```python
+# Define conversation
+messages = [
+    {"role": "system", "content": "You are Lily, a friendly assistant who loves nature."},
+    {"role": "user", "content": "What's your favorite flower?"}
+]
+
+# Apply chat template
+text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+
+# Tokenize and generate
+model_inputs = tokenizer([text], return_tensors="pt")
+generated_ids = model.generate(model_inputs.input_ids, max_new_tokens=100)
+
+# Decode response
+response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
+print(response)
+```
+
+**Expected Output** (example):
+> Oh, I adore cherry blossoms! Their delicate pink petals remind me of spring's gentle embrace.
+
+### 4. Language Translation
+
+Translate text into another language:
+
+```python
+# Define translation prompt
+prompt = "Translate 'The garden blooms with vibrant colors' into Chinese."
+
+messages = [
+    {"role": "system", "content": "You are a multilingual assistant."},
+    {"role": "user", "content": prompt}
+]
+
+# Apply chat template
+text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+
+# Tokenize and generate
+model_inputs = tokenizer([text], return_tensors="pt")
+generated_ids = model.generate(model_inputs.input_ids, max_new_tokens=50)
+
+# Decode response
+response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
+print(response)
+```
+
+**Expected Output** (example):
+> 花园盛开着鲜艳的色彩。
+
+### 5. Fine-Tuning the Model
+
+For custom tasks, fine-tune the model using Supervised Fine-Tuning (SFT):
+
+```python
+from transformers import Trainer, TrainingArguments, DataCollatorForLanguageModeling
+from datasets import load_dataset
+
+# Load dataset
+dataset = load_dataset("your_dataset")
+
+# Define training arguments
+training_args = TrainingArguments(
+    output_dir="./lily-finetuned",
+    per_device_train_batch_size=4,
+    num_train_epochs=3,
+    learning_rate=5e-5,
+)
+
+# Initialize trainer
+trainer = Trainer(
+    model=model,
+    args=training_args,
+    train_dataset=dataset["train"],
+    data_collator=DataCollatorForLanguageModeling(tokenizer=tokenizer, mlm=False),
+)
+
+# Start fine-tuning
+trainer.train()
+```
+
+## Limitations
+
+- **Context Length**: Supports up to 32K tokens, which may be insufficient for extremely long documents.
+- **GQA Support**: Lacks General Question Answering (GQA) support for most model sizes, potentially limiting performance on complex queries.
+- **Common Sense**: May occasionally miss nuanced human behavior or real-world context.
+
+## Resources
+
+- [Hugging Face Model Hub](https://huggingface.co/kulia-moon/Lily-Qwen1.5-0.5B)
+- [Qwen1.5 Documentation](https://qwenlm.github.io)
+- [Transformers Library](https://huggingface.co/docs/transformers)
+
+## Citation `BETA`
+
+If you use Lily-Qwen1.5-0.5B in your work, please cite:
+
+```bibtex
+@misc{lily-qwen1.5-0.5b,
+  author = {kulia-moon},
+  title = {Lily-Qwen1.5-0.5B: A Fine-Tuned Qwen1.5 Model},
+  year = {2025},
+  publisher = {Hugging Face},
+  journal = {Hugging Face Model Hub}
+}
+```
+
+Enjoy exploring the capabilities of **Lily-Qwen1.5-0.5B** and bring your creative ideas to life!

added_tokens.json

@@ -0,0 +1,5 @@
+{
+  "<|endoftext|>": 151643,
+  "<|im_end|>": 151645,
+  "<|im_start|>": 151644
+}

config.json

@@ -0,0 +1,28 @@
+{
+  "architectures": [
+    "Qwen2ForCausalLM"
+  ],
+  "attention_dropout": 0.0,
+  "bos_token_id": 151643,
+  "eos_token_id": 151643,
+  "hidden_act": "silu",
+  "hidden_size": 1024,
+  "initializer_range": 0.02,
+  "intermediate_size": 2816,
+  "max_position_embeddings": 32768,
+  "max_window_layers": 21,
+  "model_type": "qwen2",
+  "num_attention_heads": 16,
+  "num_hidden_layers": 24,
+  "num_key_value_heads": 16,
+  "rms_norm_eps": 1e-06,
+  "rope_scaling": null,
+  "rope_theta": 1000000.0,
+  "sliding_window": 32768,
+  "tie_word_embeddings": true,
+  "torch_dtype": "float32",
+  "transformers_version": "4.51.3",
+  "use_cache": true,
+  "use_sliding_window": false,
+  "vocab_size": 151936
+}

generation_config.json

@@ -0,0 +1,6 @@
+{
+  "bos_token_id": 151643,
+  "eos_token_id": 151643,
+  "max_new_tokens": 2048,
+  "transformers_version": "4.51.3"
+}

model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:cbea46d60f314c934242e0886778861bc25feefc29eb5b3bfe633b89a52c9197
+size 1855983640

special_tokens_map.json

@@ -0,0 +1,20 @@
+{
+  "additional_special_tokens": [
+    "<|im_start|>",
+    "<|im_end|>"
+  ],
+  "eos_token": {
+    "content": "<|endoftext|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "<|endoftext|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer.json

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:eea7366350c94ac706bb8d4bea5cd2eb07167563a7246291f6a0962dedaadcd8
+size 11418544

tokenizer_config.json

@@ -0,0 +1,44 @@
+{
+  "add_prefix_space": false,
+  "added_tokens_decoder": {
+    "151643": {
+      "content": "<|endoftext|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151644": {
+      "content": "<|im_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151645": {
+      "content": "<|im_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "additional_special_tokens": [
+    "<|im_start|>",
+    "<|im_end|>"
+  ],
+  "bos_token": null,
+  "chat_template": "{% for message in messages %}{% if loop.first and messages[0]['role'] != 'system' %}{{ '<|im_start|>system\nYou are a helpful assistant<|im_end|>\n' }}{% endif %}{{'<|im_start|>' + message['role'] + '\n' + message['content'] + '<|im_end|>' + '\n'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant\n' }}{% endif %}",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|endoftext|>",
+  "errors": "replace",
+  "extra_special_tokens": {},
+  "model_max_length": 32768,
+  "pad_token": "<|endoftext|>",
+  "split_special_tokens": false,
+  "tokenizer_class": "Qwen2Tokenizer",
+  "unk_token": null
+}