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Model: prithivMLmods/Magellanic-Qwen-14B-R1 Source: Original Platform
2026-07-08 23:52:07 +08:00
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--- a/README.md
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+---
+license: apache-2.0
+language:
+- en
+- zh
+base_model:
+- deepseek-ai/DeepSeek-R1-Distill-Qwen-14B
+pipeline_tag: text-generation
+library_name: transformers
+tags:
+- text-generation-inference
+- math
+- code
+- reasoning
+- R1
+---
+
+![vvvvvvvvvvv.png](https://cdn-uploads.huggingface.co/production/uploads/65bb837dbfb878f46c77de4c/cFNcCXQNciTqiIqEdtggJ.png)
+
+# **Magellanic-Qwen-14B-R1**
+
+> **Magellanic-Qwen-14B-R1** is based on the **DeepSeek-R1-Distill-Qwen-14B** modality architecture, enhanced specifically for **mathematical reasoning** and **coding reasoning**. This model advances the capabilities of 14B-parameter architectures, excelling in logic-based problem solving, programming tasks, and context-rich dialogue generation. It is fine-tuned with extended chain-of-thought reasoning and domain-specific datasets for improved comprehension, structured generation, and precision in technical tasks.
+
+## **Key Improvements**
+1. **Mathematical Reasoning Enhancements**  
+   Optimized with datasets targeting arithmetic, algebra, calculus, and formal logic, improving step-by-step solution generation and explanation accuracy.  
+
+2. **Coding Reasoning Enhancements**  
+   Fine-tuned on diverse programming languages and reasoning-based coding problems (e.g., LeetCode, Codeforces, and real-world engineering tasks), significantly improving code generation, debugging, and documentation.  
+
+3. **Enhanced General Knowledge**  
+   Broad knowledge base across various domains enables accurate and coherent responses for diverse topics.  
+
+4. **Improved Instruction Following**  
+   Better handling of complex, multi-step instructions with structured and logically coherent outputs.  
+
+5. **Versatile Adaptability**  
+   Resilient across open-ended and structured prompts, adapting well to different interaction styles and subject areas.  
+
+6. **Long-Context Support**  
+   Supports up to **128K tokens** of input context and can generate up to **8K tokens** of output—ideal for in-depth technical and academic outputs.  
+
+## **Quickstart with transformers**
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_name = "prithivMLmods/Magellanic-Qwen-14B-R1"
+
+model = AutoModelForCausalLM.from_pretrained(
+    model_name,
+    torch_dtype="auto",
+    device_map="auto"
+)
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+
+prompt = "Explain how quicksort works with an example in Python."
+messages = [
+    {"role": "system", "content": "You are a helpful assistant skilled in coding and reasoning tasks."},
+    {"role": "user", "content": prompt}
+]
+text = tokenizer.apply_chat_template(
+    messages,
+    tokenize=False,
+    add_generation_prompt=True
+)
+model_inputs = tokenizer([text], return_tensors="pt").to(model.device)
+
+generated_ids = model.generate(
+    **model_inputs,
+    max_new_tokens=512
+)
+generated_ids = [
+    output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
+]
+
+response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
+```
+
+## **Intended Use**
+
+1. **Mathematics and Logic Tasks**  
+   Solve and explain math problems, logical puzzles, and formula-based reasoning tasks step-by-step.  
+
+2. **Programming and Development**  
+   Assist in generating code, debugging, documenting functions, and solving algorithmic problems across multiple languages.  
+
+3. **General-Purpose Reasoning**  
+   Handle a wide variety of questions with accurate, contextual responses based on general knowledge and logic.  
+
+4. **Educational Assistance**  
+   Help students and educators with clear, structured explanations in STEM and non-STEM subjects.  
+
+5. **Conversational AI & Chatbots**  
+   Power intelligent assistants that require contextual awareness and technically sound responses.  
+
+6. **Multilingual Applications**  
+   Translate, summarize, and generate multilingual content for global users.  
+
+7. **Long-Form Content Generation**  
+   Generate coherent long articles, research summaries, and reports, especially with structured technical content.
+
+## **Limitations**
+
+1. **High Resource Usage**  
+   Requires high-memory GPUs/TPUs for efficient inference, especially when utilizing 128K context.  
+
+2. **Bias and Hallucination Risk**  
+   May reflect biases from pretraining data and occasionally hallucinate plausible-sounding but incorrect facts.  
+
+3. **Variability in Creative Tasks**  
+   Less consistent in producing high-quality creative writing or highly subjective content.  
+
+4. **Training Cutoff Constraints**  
+   No access to real-world events beyond the last training snapshot.  
+
+5. **Error Propagation in Long Outputs**  
+   Minor early mistakes can compound in very long outputs.  
+
+6. **Prompt Sensitivity**  
+   Performance may vary depending on prompt clarity and structure.
--- a/config.json
+++ b/config.json
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+{
+  "architectures": [
+    "Qwen2ForCausalLM"
+  ],
+  "attention_dropout": 0.0,
+  "bos_token_id": 151643,
+  "eos_token_id": 151643,
+  "hidden_act": "silu",
+  "hidden_size": 5120,
+  "initializer_range": 0.02,
+  "intermediate_size": 13824,
+  "max_position_embeddings": 131072,
+  "max_window_layers": 48,
+  "model_type": "qwen2",
+  "num_attention_heads": 40,
+  "num_hidden_layers": 48,
+  "num_key_value_heads": 8,
+  "rms_norm_eps": 1e-05,
+  "rope_scaling": null,
+  "rope_theta": 1000000.0,
+  "sliding_window": 131072,
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.51.1",
+  "use_cache": true,
+  "use_sliding_window": false,
+  "vocab_size": 152064
+}
--- a/configuration.json
+++ b/configuration.json
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+{"framework": "pytorch", "task": "others", "allow_remote": true}
--- a/generation_config.json
+++ b/generation_config.json
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+{
+  "_from_model_config": true,
+  "bos_token_id": 151646,
+  "eos_token_id": 151643,
+  "do_sample": true,
+  "temperature": 0.6,
+  "top_p": 0.95,
+  "transformers_version": "4.51.1"
+}
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+{
+  "add_bos_token": true,
+  "add_eos_token": false,
+  "bos_token": {
+    "__type": "AddedToken",
+    "content": "<｜begin▁of▁sentence｜>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  },
+  "clean_up_tokenization_spaces": false,
+  "eos_token": {
+    "__type": "AddedToken",
+    "content": "<｜end▁of▁sentence｜>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  },
+  "legacy": true,
+  "model_max_length": 16384,
+  "pad_token": {
+    "__type": "AddedToken",
+    "content": "<｜end▁of▁sentence｜>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  },
+  "sp_model_kwargs": {},
+  "unk_token": null,
+  "tokenizer_class": "LlamaTokenizerFast",
+  "chat_template": "{% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{% set ns = namespace(is_first=false, is_tool=false, is_output_first=true, system_prompt='') %}{%- for message in messages %}{%- if message['role'] == 'system' %}{% set ns.system_prompt = message['content'] %}{%- endif %}{%- endfor %}{{bos_token}}{{ns.system_prompt}}{%- for message in messages %}{%- if message['role'] == 'user' %}{%- set ns.is_tool = false -%}{{'<｜User｜>' + message['content']}}{%- endif %}{%- if message['role'] == 'assistant' and message['content'] is none %}{%- set ns.is_tool = false -%}{%- for tool in message['tool_calls']%}{%- if not ns.is_first %}{{'<｜Assistant｜><｜tool▁calls▁begin｜><｜tool▁call▁begin｜>' + tool['type'] + '<｜tool▁sep｜>' + tool['function']['name'] + '\\n' + '```json' + '\\n' + tool['function']['arguments'] + '\\n' + '```' + '<｜tool▁call▁end｜>'}}{%- set ns.is_first = true -%}{%- else %}{{'\\n' + '<｜tool▁call▁begin｜>' + tool['type'] + '<｜tool▁sep｜>' + tool['function']['name'] + '\\n' + '```json' + '\\n' + tool['function']['arguments'] + '\\n' + '```' + '<｜tool▁call▁end｜>'}}{{'<｜tool▁calls▁end｜><｜end▁of▁sentence｜>'}}{%- endif %}{%- endfor %}{%- endif %}{%- if message['role'] == 'assistant' and message['content'] is not none %}{%- if ns.is_tool %}{{'<｜tool▁outputs▁end｜>' + message['content'] + '<｜end▁of▁sentence｜>'}}{%- set ns.is_tool = false -%}{%- else %}{% set content = message['content'] %}{% if '</think>' in content %}{% set content = content.split('</think>')[-1] %}{% endif %}{{'<｜Assistant｜>' + content + '<｜end▁of▁sentence｜>'}}{%- endif %}{%- endif %}{%- if message['role'] == 'tool' %}{%- set ns.is_tool = true -%}{%- if ns.is_output_first %}{{'<｜tool▁outputs▁begin｜><｜tool▁output▁begin｜>' + message['content'] + '<｜tool▁output▁end｜>'}}{%- set ns.is_output_first = false %}{%- else %}{{'\\n<｜tool▁output▁begin｜>' + message['content'] + '<｜tool▁output▁end｜>'}}{%- endif %}{%- endif %}{%- endfor -%}{% if ns.is_tool %}{{'<｜tool▁outputs▁end｜>'}}{% endif %}{% if add_generation_prompt and not ns.is_tool %}{{'<｜Assistant｜><think>\\n'}}{% endif %}"
+}
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