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Model: prithivMLmods/Llama-3.2-3B-Math-Oct Source: Original Platform
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README.md
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README.md
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---
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license: llama3.2
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language:
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- en
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base_model:
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- meta-llama/Llama-3.2-3B-Instruct
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pipeline_tag: text-generation
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library_name: transformers
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tags:
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- text-generation-inference
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---
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# **Llama-3.2-3B-Math-Oct**
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Llama-3.2-3B-Math-Oct is a math role-play model designed to solve mathematical problems and enhance the reasoning capabilities of 3B-parameter models. These models have proven highly effective in context understanding, reasoning, and mathematical problem-solving, based on the Llama 3.2 is an auto-regressive language model that uses an optimized transformer architecture. The tuned versions use supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF) to align with human preferences for helpfulness and safety.
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# **Use with transformers**
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Starting with `transformers >= 4.43.0` onward, you can run conversational inference using the Transformers `pipeline` abstraction or by leveraging the Auto classes with the `generate()` function.
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Make sure to update your transformers installation via `pip install --upgrade transformers`.
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```python
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import torch
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from transformers import pipeline
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model_id = "prithivMLmods/Llama-3.2-3B-Math-Oct"
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pipe = pipeline(
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"text-generation",
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model=model_id,
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torch_dtype=torch.bfloat16,
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device_map="auto",
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)
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messages = [
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{"role": "system", "content": "You are a pirate chatbot who always responds in pirate speak!"},
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{"role": "user", "content": "Who are you?"},
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]
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outputs = pipe(
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messages,
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max_new_tokens=256,
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)
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print(outputs[0]["generated_text"][-1])
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```
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# **Intended Use**
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1. **Mathematical Problem Solving**: Llama-3.2-3B-Math-Oct is designed for solving a wide range of mathematical problems, including arithmetic, algebra, calculus, and probability.
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2. **Reasoning Enhancement**: It enriches logical reasoning capabilities, helping users understand and solve complex mathematical concepts.
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3. **Context Understanding**: The model is highly effective in interpreting problem statements, mathematical scenarios, and context-heavy equations.
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4. **Educational Support**: It serves as a learning tool for students, educators, and enthusiasts, providing step-by-step explanations for mathematical solutions.
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5. **Scenario Simulation**: The model can role-play specific mathematical scenarios, such as tutoring, creating math problems, or acting as a math assistant.
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# **Limitations**
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1. **Accuracy Constraints**: While effective in many cases, the model may occasionally provide incorrect solutions, particularly for highly complex or unconventional problems.
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2. **Parameter Limitation**: Being a 3B-parameter model, it might lack the precision and capacity of larger models for intricate problem-solving.
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3. **Lack of Domain-Specific Expertise**: The model may struggle with problems requiring niche mathematical knowledge or specialized fields like advanced topology or quantum mechanics.
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4. **Dependency on Input Clarity**: Ambiguous or poorly worded problem statements might lead to incorrect interpretations and solutions.
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5. **Inability to Learn Dynamically**: The model cannot improve its understanding or reasoning dynamically without retraining.
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6. **Non-Mathematical Queries**: While optimized for mathematics, the model may underperform in general-purpose tasks compared to models designed for broader use cases.
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7. **Computational Resources**: Deploying the model may require significant computational resources for real-time usage.
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config.json
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config.json
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{
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"architectures": [
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"LlamaForCausalLM"
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],
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"attention_bias": false,
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"attention_dropout": 0.0,
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"bos_token_id": 128000,
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"eos_token_id": 128009,
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"head_dim": 128,
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"hidden_act": "silu",
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"hidden_size": 3072,
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"initializer_range": 0.02,
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"intermediate_size": 8192,
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"max_position_embeddings": 131072,
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"mlp_bias": false,
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"model_type": "llama",
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"num_attention_heads": 24,
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"num_hidden_layers": 28,
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"num_key_value_heads": 8,
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"pretraining_tp": 1,
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"rms_norm_eps": 1e-05,
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"rope_scaling": {
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"factor": 32.0,
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"high_freq_factor": 4.0,
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"low_freq_factor": 1.0,
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"rope_type": "llama3"
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"vocab_size": 128256
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}
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configuration.json
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||||
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||||
23
special_tokens_map.json
Normal file
23
special_tokens_map.json
Normal file
@@ -0,0 +1,23 @@
|
||||
{
|
||||
"bos_token": {
|
||||
"content": "<|begin_of_text|>",
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
},
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
},
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
}
|
||||
}
|
||||
BIN
tokenizer.json
(Stored with Git LFS)
Normal file
BIN
tokenizer.json
(Stored with Git LFS)
Normal file
Binary file not shown.
2067
tokenizer_config.json
Normal file
2067
tokenizer_config.json
Normal file
File diff suppressed because it is too large
Load Diff
Reference in New Issue
Block a user