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Model: prithivMLmods/Lambda-Cancri-1.5B-Exp Source: Original Platform
2026-09-09 05:41:11 +08:00
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+---
+library_name: transformers
+tags:
+- text-generation-inference
+- code
+- math
+- sft
+license: apache-2.0
+language:
+- en
+base_model:
+- Qwen/Qwen2.5-1.5B-Instruct
+pipeline_tag: text-generation
+---
+
+![5.png](https://cdn-uploads.huggingface.co/production/uploads/65bb837dbfb878f46c77de4c/oRjYbuQFy0ajchUguRXKO.png)
+
+# **Lambda-Cancri-1.5B-Exp**
+
+> **Lambda-Cancri-1.5B-Exp** is a **general-purpose LLM** fine-tuned from **Qwen2.5-1.5B** using **optimized supervised fine-tuning (SFT)**. This model is designed to enhance coding proficiency, reasoning ability, and step-by-step explanation across multiple software development and general knowledge tasks.
+
+## **Key Features**
+
+1. **Code Reasoning & Explanation**  
+   Trained to **analyze, generate, and explain** code with a focus on logic, structure, and clarity. Supports functional, object-oriented, and procedural paradigms.
+
+2. **Optimized Supervised Fine-Tuning (SFT)**  
+   Fine-tuned using **high-quality supervised datasets**, ensuring strong performance in tasks like code generation, bug fixing, function completion, and abstract reasoning.
+
+3. **Multi-Language & General Task Support**  
+   Works fluently with **Python**, **JavaScript**, **C++**, **Shell**, and general knowledge tasks — ideal for programming, scripting, algorithmic problem-solving, and general-purpose reasoning.
+
+4. **Compact and Efficient**  
+   At just **1.5B parameters**, it's lightweight enough for **edge deployments**, **developer tools**, and **general-purpose assistants**, while maintaining strong reasoning and coding capabilities.
+
+5. **Debugging and Auto-Fix Capabilities**  
+   Built to **identify bugs**, **recommend corrections**, and provide **context-aware explanations** of issues across a wide range of codebases.
+
+## **Quickstart with Transformers**
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_name = "prithivMLmods/Lambda-Cancri-1.5B-Exp"
+
+model = AutoModelForCausalLM.from_pretrained(
+    model_name,
+    torch_dtype="auto",
+    device_map="auto"
+)
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+
+prompt = "Write a Python function that checks if a number is prime, and explain how it works."
+
+messages = [
+    {"role": "system", "content": "You are a helpful coding and reasoning assistant. Your job is to write correct code and explain the logic step-by-step."},
+    {"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**
+
+- **Code Assistance & IDE Integration**:  
+  Smart autocomplete, bug detection, function suggestion, and explanations for developers.
+
+- **Learning & Education**:  
+  Perfect for **students**, **educators**, and **self-learners** in programming and technical fields.
+
+- **Automated Code Review & QA**:  
+  Assists in logic analysis, structure evaluation, and bug spotting in code for quality assurance.
+
+- **General Purpose Assistant**:  
+  Provides help beyond coding—answering general queries, solving reasoning tasks, and assisting in workflows.
+
+- **Edge & DevTool Deployments**:  
+  Lightweight for browser extensions, desktop applications, and CLI-based assistants.
+
+## **Limitations**
+
+1. **Scaling Challenges**  
+   May not handle extremely large or highly complex projects as well as larger models.
+
+2. **Creativity Variability**  
+   May show inconsistent performance on highly creative or unconventional coding tasks.
+
+3. **Security Considerations**  
+   Outputs should be audited to ensure the generation of secure, safe code.
+
+4. **Instruction Sensitivity**  
+   Responds better with clear, structured prompts and task instructions.