Text Generation
Transformers
Safetensors
qwen2
code-generation
nl2python
java2python
code2doc
multitask
conversational
text-generation-inference
Instructions to use Saikrishna2511/qwen-multitask with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Saikrishna2511/qwen-multitask with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Saikrishna2511/qwen-multitask") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Saikrishna2511/qwen-multitask") model = AutoModelForCausalLM.from_pretrained("Saikrishna2511/qwen-multitask") messages = [ {"role": "user", "content": "Who are you?"}, ] inputs = tokenizer.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=40) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Saikrishna2511/qwen-multitask with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Saikrishna2511/qwen-multitask" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Saikrishna2511/qwen-multitask", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/Saikrishna2511/qwen-multitask
- SGLang
How to use Saikrishna2511/qwen-multitask with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "Saikrishna2511/qwen-multitask" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Saikrishna2511/qwen-multitask", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "Saikrishna2511/qwen-multitask" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Saikrishna2511/qwen-multitask", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use Saikrishna2511/qwen-multitask with Docker Model Runner:
docker model run hf.co/Saikrishna2511/qwen-multitask
Upload folder using huggingface_hub
Browse files- .gitattributes +1 -0
- README.md +89 -0
- chat_template.jinja +54 -0
- config.json +57 -0
- generation_config.json +14 -0
- model.safetensors +3 -0
- tokenizer.json +3 -0
- tokenizer_config.json +30 -0
.gitattributes
CHANGED
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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tokenizer.json filter=lfs diff=lfs merge=lfs -text
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README.md
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@@ -0,0 +1,89 @@
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---
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license: apache-2.0
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base_model: Qwen/Qwen2.5-Coder-0.5B-Instruct
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tags:
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- code-generation
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- qwen2
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- nl2python
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- java2python
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- code2doc
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- multitask
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library_name: transformers
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pipeline_tag: text-generation
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---
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# Saikrishna2511/qwen-multitask
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Multi-task fine-tuned **Qwen2.5-Coder-0.5B-Instruct** checkpoint for code generation and documentation.
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## Demo
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Try the model in the browser: [https://huggingface.co/spaces/Saikrishna2511/qwen-multitask-demo](https://huggingface.co/spaces/Saikrishna2511/qwen-multitask-demo)
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## Tasks
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This single checkpoint handles three tasks via different prompt prefixes:
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### NL → Python (`nl2py`)
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```
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### Instruction: Write Python for: {natural language description}
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### Response:
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```
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### Java → Python (`java2py`)
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```
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### Translate Java to Python:
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```java
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{java code}
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```
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### Python:
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```python
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```
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### Code → Documentation (`code2doc`)
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```
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### Generate documentation for this Python code:
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```python
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{python code}
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```
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### Documentation:
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```
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## Training
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- **Base model:** [Qwen/Qwen2.5-Coder-0.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-Coder-0.5B-Instruct)
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- **Stage 1:** Java→Python LoRA fine-tune on AVATAR-TC
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- **Stage 2:** Multi-task LoRA on NL2Py, Code2Doc, code comments, and Java2Py replay
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- **Method:** LoRA (r=16, alpha=32), merged weights for inference
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## Usage
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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import torch
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model_id = "Saikrishna2511/qwen-multitask"
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tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
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model = AutoModelForCausalLM.from_pretrained(
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model_id,
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trust_remote_code=True,
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torch_dtype=torch.float16,
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device_map="auto",
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)
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prompt = "### Instruction: Write Python for: return the factorial of n\n### Response:\n"
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inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
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outputs = model.generate(**inputs, max_new_tokens=512, temperature=0.2, top_p=0.95)
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print(tokenizer.decode(outputs[0], skip_special_tokens=True))
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```
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For post-processing and all three task templates, see the [project repo](https://github.com) or the linked Gradio Space.
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## Limitations
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| 86 |
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- Small 0.5B model; quality varies by task and input complexity
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- Trained primarily on Python; Java translation quality depends on training coverage
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- Not intended for production use without further evaluation
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chat_template.jinja
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{%- if tools %}
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{{- '<|im_start|>system\n' }}
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{%- if messages[0]['role'] == 'system' %}
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{{- messages[0]['content'] }}
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{%- else %}
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{{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}
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{%- endif %}
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{{- "\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>" }}
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{%- for tool in tools %}
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{{- "\n" }}
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{{- tool | tojson }}
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{%- endfor %}
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{{- "\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" }}
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{%- else %}
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{%- if messages[0]['role'] == 'system' %}
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{{- '<|im_start|>system\n' + messages[0]['content'] + '<|im_end|>\n' }}
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{%- else %}
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{{- '<|im_start|>system\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\n' }}
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{%- endif %}
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{%- endif %}
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{%- for message in messages %}
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{%- if (message.role == "user") or (message.role == "system" and not loop.first) or (message.role == "assistant" and not message.tool_calls) %}
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{{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
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{%- elif message.role == "assistant" %}
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{{- '<|im_start|>' + message.role }}
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{%- if message.content %}
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{{- '\n' + message.content }}
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{%- endif %}
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{%- for tool_call in message.tool_calls %}
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{%- if tool_call.function is defined %}
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{%- set tool_call = tool_call.function %}
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{%- endif %}
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{{- '\n<tool_call>\n{"name": "' }}
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{{- tool_call.name }}
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{{- '", "arguments": ' }}
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{{- tool_call.arguments | tojson }}
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{{- '}\n</tool_call>' }}
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{%- endfor %}
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{{- '<|im_end|>\n' }}
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{%- elif message.role == "tool" %}
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{%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != "tool") %}
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{{- '<|im_start|>user' }}
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{%- endif %}
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{{- '\n<tool_response>\n' }}
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{{- message.content }}
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{{- '\n</tool_response>' }}
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{%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
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{{- '<|im_end|>\n' }}
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{%- endif %}
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{%- endif %}
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{%- endfor %}
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{%- if add_generation_prompt %}
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{{- '<|im_start|>assistant\n' }}
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{%- endif %}
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config.json
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{
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| 2 |
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"architectures": [
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| 3 |
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"Qwen2ForCausalLM"
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| 4 |
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],
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| 5 |
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"attention_dropout": 0.0,
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| 6 |
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"bos_token_id": 151643,
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| 7 |
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"dtype": "bfloat16",
|
| 8 |
+
"eos_token_id": 151645,
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| 9 |
+
"hidden_act": "silu",
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| 10 |
+
"hidden_size": 896,
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| 11 |
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"initializer_range": 0.02,
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| 12 |
+
"intermediate_size": 4864,
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| 13 |
+
"layer_types": [
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| 14 |
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"full_attention",
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| 15 |
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"full_attention",
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| 16 |
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"full_attention",
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| 17 |
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"full_attention",
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| 18 |
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"full_attention",
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| 19 |
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"full_attention",
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| 20 |
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"full_attention",
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| 21 |
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"full_attention",
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| 22 |
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"full_attention",
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| 23 |
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"full_attention",
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| 24 |
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"full_attention",
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| 25 |
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"full_attention",
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| 26 |
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"full_attention",
|
| 27 |
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"full_attention",
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| 28 |
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"full_attention",
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| 29 |
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"full_attention",
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| 30 |
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"full_attention",
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| 31 |
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"full_attention",
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| 32 |
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"full_attention",
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| 33 |
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"full_attention",
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| 34 |
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"full_attention",
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| 35 |
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"full_attention",
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| 36 |
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"full_attention",
|
| 37 |
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"full_attention"
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| 38 |
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],
|
| 39 |
+
"max_position_embeddings": 32768,
|
| 40 |
+
"max_window_layers": 24,
|
| 41 |
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"model_type": "qwen2",
|
| 42 |
+
"num_attention_heads": 14,
|
| 43 |
+
"num_hidden_layers": 24,
|
| 44 |
+
"num_key_value_heads": 2,
|
| 45 |
+
"pad_token_id": null,
|
| 46 |
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"rms_norm_eps": 1e-06,
|
| 47 |
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"rope_parameters": {
|
| 48 |
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"rope_theta": 1000000.0,
|
| 49 |
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"rope_type": "default"
|
| 50 |
+
},
|
| 51 |
+
"sliding_window": null,
|
| 52 |
+
"tie_word_embeddings": true,
|
| 53 |
+
"transformers_version": "5.10.2",
|
| 54 |
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"use_cache": true,
|
| 55 |
+
"use_sliding_window": false,
|
| 56 |
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"vocab_size": 151936
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| 57 |
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}
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generation_config.json
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{
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"bos_token_id": 151643,
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| 3 |
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"do_sample": true,
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| 4 |
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"eos_token_id": [
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| 5 |
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151645,
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| 6 |
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151643
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| 7 |
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],
|
| 8 |
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"pad_token_id": 151643,
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| 9 |
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"repetition_penalty": 1.05,
|
| 10 |
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"temperature": 0.7,
|
| 11 |
+
"top_k": 20,
|
| 12 |
+
"top_p": 0.8,
|
| 13 |
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"transformers_version": "5.10.2"
|
| 14 |
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}
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model.safetensors
ADDED
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| 1 |
+
version https://git-lfs.github.com/spec/v1
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| 2 |
+
oid sha256:e110ae439e03dc153ff65366483670696f1d95f1a4f3e37a9cfd3eab23a437bd
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| 3 |
+
size 988097824
|
tokenizer.json
ADDED
|
@@ -0,0 +1,3 @@
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|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:3fd169731d2cbde95e10bf356d66d5997fd885dd8dbb6fb4684da3f23b2585d8
|
| 3 |
+
size 11421892
|
tokenizer_config.json
ADDED
|
@@ -0,0 +1,30 @@
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|
| 1 |
+
{
|
| 2 |
+
"add_prefix_space": false,
|
| 3 |
+
"backend": "tokenizers",
|
| 4 |
+
"bos_token": null,
|
| 5 |
+
"clean_up_tokenization_spaces": false,
|
| 6 |
+
"eos_token": "<|im_end|>",
|
| 7 |
+
"errors": "replace",
|
| 8 |
+
"extra_special_tokens": [
|
| 9 |
+
"<|im_start|>",
|
| 10 |
+
"<|im_end|>",
|
| 11 |
+
"<|object_ref_start|>",
|
| 12 |
+
"<|object_ref_end|>",
|
| 13 |
+
"<|box_start|>",
|
| 14 |
+
"<|box_end|>",
|
| 15 |
+
"<|quad_start|>",
|
| 16 |
+
"<|quad_end|>",
|
| 17 |
+
"<|vision_start|>",
|
| 18 |
+
"<|vision_end|>",
|
| 19 |
+
"<|vision_pad|>",
|
| 20 |
+
"<|image_pad|>",
|
| 21 |
+
"<|video_pad|>"
|
| 22 |
+
],
|
| 23 |
+
"is_local": true,
|
| 24 |
+
"local_files_only": false,
|
| 25 |
+
"model_max_length": 32768,
|
| 26 |
+
"pad_token": "<|endoftext|>",
|
| 27 |
+
"split_special_tokens": false,
|
| 28 |
+
"tokenizer_class": "Qwen2Tokenizer",
|
| 29 |
+
"unk_token": null
|
| 30 |
+
}
|