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Model: prithivMLmods/Llama-Thinker-3B-Preview2 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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library_name: transformers
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tags:
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- deep_think
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- reasoning
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- chain_of_thought
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- chain_of_thinking
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- prev_2
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- self_reasoning
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language:
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- en
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base_model:
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- prithivMLmods/Llama-Thinker-3B-Preview
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pipeline_tag: text-generation
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---
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# **Llama-Thinker-3B-Preview2**
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Llama-Thinker-3B-Preview2 is a pretrained and instruction-tuned generative model designed for multilingual applications. These models are trained using synthetic datasets based on long chains of thought, enabling them to perform complex reasoning tasks effectively.
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Model Architecture: [ Based on Llama 3.2 ] is an autoregressive language model that uses an optimized transformer architecture. The tuned versions undergo 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-Thinker-3B-Preview2"
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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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Note: You can also find detailed recipes on how to use the model locally, with `torch.compile()`, assisted generations, quantised and more at [`huggingface-llama-recipes`](https://github.com/huggingface/huggingface-llama-recipes)
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# **Use with `llama`**
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Please, follow the instructions in the [repository](https://github.com/meta-llama/llama)
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To download Original checkpoints, see the example command below leveraging `huggingface-cli`:
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```
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huggingface-cli download prithivMLmods/Llama-Thinker-3B-Preview2 --include "original/*" --local-dir Llama-Thinker-3B-Preview2
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```
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Here’s a version tailored for the **Llama-Thinker-3B-Preview2-GGUF** model:
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---
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# **How to Run Llama-Thinker-3B-Preview2 on Ollama Locally**
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This guide demonstrates how to run the **Llama-Thinker-3B-Preview2-GGUF** model locally using Ollama. The model is instruction-tuned for multilingual tasks and complex reasoning, making it highly versatile for a wide range of use cases. By the end, you'll be equipped to run this and other open-source models with ease.
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---
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## Example 1: How to Run the Llama-Thinker-3B-Preview2 Model
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The **Llama-Thinker-3B-Preview2** model is a pretrained and instruction-tuned LLM, designed for complex reasoning tasks across multiple languages. In this guide, we'll interact with it locally using Ollama, with support for quantized models.
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### Step 1: Download the Model
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First, download the **Llama-Thinker-3B-Preview2-GGUF** model using the following command:
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```bash
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ollama run llama-thinker-3b-preview2.gguf
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```
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### Step 2: Model Initialization and Download
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Once the command is executed, Ollama will initialize and download the necessary model files. You should see output similar to this:
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```plaintext
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pulling manifest
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pulling a12cd3456efg... 100% ▕██████████████████████████████████████████████████████████████████████████████████████████▏ 3.2 GB
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pulling 9f87ghijklmn... 100% ▕██████████████████████████████████████████████████████████████████████████████████████████▏ 6.5 KB
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verifying sha256 digest
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writing manifest
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removing any unused layers
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success
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>>> Send a message (/? for help)
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```
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### Step 3: Interact with the Model
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Once the model is fully loaded, you can interact with it by sending prompts. For example, let's ask:
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```plaintext
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>>> How can you assist me today?
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```
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A sample response might look like this [may / maynot be identical]:
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```plaintext
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I am Llama-Thinker-3B-Preview2, an advanced AI language model designed to assist with complex reasoning, multilingual tasks, and general-purpose queries. Here are a few things I can help you with:
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1. Answering complex questions in multiple languages.
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2. Assisting with creative writing, content generation, and problem-solving.
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3. Providing detailed summaries and explanations.
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4. Translating text across different languages.
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5. Generating ideas for personal or professional use.
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6. Offering insights on technical topics.
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Feel free to ask me anything you'd like assistance with!
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```
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### Step 4: Exit the Program
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To exit the program, simply type:
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```plaintext
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/exit
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```
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---
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## Example 2: Using Multi-Modal Models (Future Use)
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In the future, Ollama may support multi-modal models where you can input both text and images for advanced interactions. This section will be updated as new capabilities become available.
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---
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## Notes on Using Quantized Models
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Quantized models like **llama-thinker-3b-preview2.gguf** are optimized for efficient performance on local systems with limited resources. Here are some key points to ensure smooth operation:
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1. **VRAM/CPU Requirements**: Ensure your system has adequate VRAM or CPU resources to handle model inference.
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2. **Model Format**: Use the `.gguf` model format for compatibility with Ollama.
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---
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# **Conclusion**
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Running the **Llama-Thinker-3B-Preview2** model locally using Ollama provides a powerful way to leverage open-source LLMs for complex reasoning and multilingual tasks. By following this guide, you can explore other models and expand your use cases as new models become available.
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---
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config.json
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"vocab_size": 128256
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}
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23
special_tokens_map.json
Normal file
23
special_tokens_map.json
Normal file
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|
||||
{
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||||
"bos_token": {
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|
||||
3
tokenizer.json
Normal file
3
tokenizer.json
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:6b9e4e7fb171f92fd137b777cc2714bf87d11576700a1dcd7a399e7bbe39537b
|
||||
size 17209920
|
||||
2065
tokenizer_config.json
Normal file
2065
tokenizer_config.json
Normal file
File diff suppressed because it is too large
Load Diff
Reference in New Issue
Block a user