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Model: prithivMLmods/Acrux-500M-o1-Journey Source: Original Platform
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README.md
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README.md
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---
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license: creativeml-openrail-m
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datasets:
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- GAIR/o1-journey
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language:
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- en
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base_model:
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- Qwen/Qwen2.5-0.5B-Instruct
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library_name: transformers
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pipeline_tag: text-generation
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tags:
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- Qwen2.5
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- Llama-Cpp
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- CoT
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- o1-journey
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- text-generation-inference
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- safetensors
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- Ollama
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---
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### Acrux-500M-o1-Journey Model Files
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The **Acrux-500M-o1-Journey** is a lightweight, instruction-tuned language model fine-tuned from the **Qwen2.5-0.5B-Instruct** base model. With a size of 500 million parameters, it is designed for **cost-effective deployment** and **fast text generation** while maintaining quality performance for instruction-following tasks.
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| **File Name** | **Size** | **Description** | **Upload Status** |
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|----------------------------|----------------|-------------------------------------------|--------------------|
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| `.gitattributes` | 1.57 kB | Git attributes for managing LFS files. | Uploaded |
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| `README.md` | 195 Bytes | Model overview or documentation. | Updated |
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| `added_tokens.json` | 657 Bytes | Custom tokens for the tokenizer. | Uploaded |
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| `config.json` | 859 Bytes | Model configuration file. | Uploaded |
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| `generation_config.json` | 280 Bytes | Configuration for text generation. | Uploaded |
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| `merges.txt` | 1.82 MB | Merge rules for byte-pair encoding (BPE). | Uploaded |
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| `pytorch_model.bin` | 988 MB | Model weights (PyTorch format). | Uploaded (LFS) |
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| `special_tokens_map.json` | 644 Bytes | Mapping for special tokens. | Uploaded |
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| `tokenizer.json` | 11.4 MB | Full tokenizer configuration. | Uploaded (LFS) |
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| `tokenizer_config.json` | 7.73 kB | Additional tokenizer settings. | Uploaded |
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| `vocab.json` | 2.78 MB | Vocabulary for the tokenizer. | Uploaded |
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### **Key Features:**
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1. **Compact Size with Efficient Performance:**
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The smaller parameter count (500M) ensures faster inference and reduced hardware requirements.
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2. **Instruction Optimization:**
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Fine-tuned to follow prompts effectively, making it suitable for interactive applications and prompt-based tasks.
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3. **Domain-Specific Training:**
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Trained on the **GAIR/o1-journey** dataset, providing tailored capabilities for specific use cases.
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---
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### **Training Details:**
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- **Base Model:** [Qwen2.5-0.5B-Instruct](#)
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- **Dataset Used for Fine-Tuning:** [GAIR/o1-journey](#)
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- A compact dataset focusing on instruction-driven generation with 1.42k samples.
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---
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### **Capabilities:**
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1. **Instruction Following:**
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- Generates accurate and coherent responses to user instructions.
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- Handles summarization, question-answering, and conversational tasks.
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2. **Fast Inference:**
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- Ideal for real-time applications due to reduced latency from its smaller size.
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3. **Interactive AI Development:**
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- Suitable for chatbots, virtual assistants, and instructional interfaces.
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---
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### **Usage Instructions:**
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1. **Setup:**
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Download all model files, ensuring compatibility with the Hugging Face Transformers library.
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2. **Loading the Model:**
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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model_name = "prithivMLmods/Acrux-500M-o1-Journey"
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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model = AutoModelForCausalLM.from_pretrained(model_name)
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```
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3. **Sample Generate Text:**
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```python
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input_text = "Explain the concept of machine learning in simple terms."
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inputs = tokenizer(input_text, return_tensors="pt")
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outputs = model.generate(**inputs, max_length=100, temperature=0.7)
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print(tokenizer.decode(outputs[0], skip_special_tokens=True))
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```
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4. **Optimize Generation:**
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Adjust parameters in `generation_config.json` for better control of output, such as:
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- `temperature` for randomness.
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- `top_p` for sampling diversity.
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- `max_length` for output size.
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---
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config.json
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||||
"additional_special_tokens": [
|
||||
"<|im_start|>",
|
||||
"<|im_end|>",
|
||||
"<|object_ref_start|>",
|
||||
"<|object_ref_end|>",
|
||||
"<|box_start|>",
|
||||
"<|box_end|>",
|
||||
"<|quad_start|>",
|
||||
"<|quad_end|>",
|
||||
"<|vision_start|>",
|
||||
"<|vision_end|>",
|
||||
"<|vision_pad|>",
|
||||
"<|image_pad|>",
|
||||
"<|video_pad|>"
|
||||
],
|
||||
"bos_token": null,
|
||||
"chat_template": "{%- if tools %}\n {{- '<|im_start|>system\\n' }}\n {%- if messages[0]['role'] == 'system' %}\n {{- messages[0]['content'] }}\n {%- else %}\n {{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}\n {%- endif %}\n {{- \"\\n\\n# Tools\\n\\nYou may call one or more functions to assist with the user query.\\n\\nYou are provided with function signatures within <tools></tools> XML tags:\\n<tools>\" }}\n {%- for tool in tools %}\n {{- \"\\n\" }}\n {{- tool | tojson }}\n {%- endfor %}\n {{- \"\\n</tools>\\n\\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\\n<tool_call>\\n{\\\"name\\\": <function-name>, \\\"arguments\\\": <args-json-object>}\\n</tool_call><|im_end|>\\n\" }}\n{%- else %}\n {%- if messages[0]['role'] == 'system' %}\n {{- '<|im_start|>system\\n' + messages[0]['content'] + '<|im_end|>\\n' }}\n {%- else %}\n {{- '<|im_start|>system\\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\\n' }}\n {%- endif %}\n{%- endif %}\n{%- for message in messages %}\n {%- if (message.role == \"user\") or (message.role == \"system\" and not loop.first) or (message.role == \"assistant\" and not message.tool_calls) %}\n {{- '<|im_start|>' + message.role + '\\n' + message.content + '<|im_end|>' + '\\n' }}\n {%- elif message.role == \"assistant\" %}\n {{- '<|im_start|>' + message.role }}\n {%- if message.content %}\n {{- '\\n' + message.content }}\n {%- endif %}\n {%- for tool_call in message.tool_calls %}\n {%- if tool_call.function is defined %}\n {%- set tool_call = tool_call.function %}\n {%- endif %}\n {{- '\\n<tool_call>\\n{\"name\": \"' }}\n {{- tool_call.name }}\n {{- '\", \"arguments\": ' }}\n {{- tool_call.arguments | tojson }}\n {{- '}\\n</tool_call>' }}\n {%- endfor %}\n {{- '<|im_end|>\\n' }}\n {%- elif message.role == \"tool\" %}\n {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != \"tool\") %} {{- '<|im_start|>user' }}\n {%- endif %}\n {{- '\\n<tool_response>\\n' }}\n {{- message.content }}\n {{- '\\n</tool_response>' }}\n {%- if loop.last or (messages[loop.index0 + 1].role != \"tool\") %}\n {{- '<|im_end|>\\n' }}\n {%- endif %}\n {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n {{- '<|im_start|>assistant\\n' }}\n{%- endif %}\n",
|
||||
"clean_up_tokenization_spaces": false,
|
||||
"eos_token": "<|im_end|>",
|
||||
"errors": "replace",
|
||||
"model_max_length": 32768,
|
||||
"pad_token": "<|PAD_TOKEN|>",
|
||||
"padding_side": "left",
|
||||
"split_special_tokens": false,
|
||||
"tokenizer_class": "Qwen2Tokenizer",
|
||||
"unk_token": null
|
||||
}
|
||||
1
vocab.json
Normal file
1
vocab.json
Normal file
File diff suppressed because one or more lines are too long
Reference in New Issue
Block a user