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Model: ruslanmv/granite-3.1-2b-Reasoning Source: Original Platform
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README.md
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README.md
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---
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base_model: ibm-granite/granite-3.1-2b-instruct
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tags:
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- text-generation-inference
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- transformers
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- granite
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- trl
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- grpo
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- ruslanmv
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license: apache-2.0
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language:
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- en
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---
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# Granite-3.1-2B-Reasoning (Fine-tuned for Logical Reasoning)
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## Model Overview
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This model is a fine-tuned version of **ibm-granite/granite-3.1-2b-instruct**, specifically optimized for **enhanced reasoning capabilities**. Fine-tuning has been conducted to improve its performance on logical reasoning, structured problem-solving, and complex analytical tasks.
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- **Developed by:** [ruslanmv](https://huggingface.co/ruslanmv)
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- **License:** Apache 2.0
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- **Base Model:** [ibm-granite/granite-3.1-2b-instruct](https://huggingface.co/ibm-granite/granite-3.1-2b-instruct)
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- **Fine-tuned for:** Logical reasoning, structured problem-solving, long-context tasks
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- **Supported Languages:** English
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---
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## Model Summary
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**Granite-3.1-2B-Reasoning** is part of IBM’s **Granite 3.1** language model series, which supports extended context lengths and strong multi-domain performance. This fine-tuned variant enhances the model's ability to process complex reasoning tasks efficiently.
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### Improvements Over Base Model:
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✅ Improved **reasoning** and **problem-solving** skills
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✅ Optimized for **instruction-following** and **logical deduction**
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✅ Maintains the **efficiency and robustness** of Granite-3.1
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---
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## Installation & Usage
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Install the required dependencies:
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```bash
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pip install torch torchvision torchaudio
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pip install accelerate
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pip install transformers
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```
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### Running the Model
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Use the following Python snippet to load and generate text with the fine-tuned model:
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer, GenerationConfig
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import torch
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# Model and tokenizer
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model_name = "ruslanmv/granite-3.1-2b-Reasoning"
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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model = AutoModelForCausalLM.from_pretrained(
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model_name,
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device_map='auto', # or 'cuda' if you have only one GPU
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torch_dtype=torch.float16, # Use float16 for faster and less memory intensive inference
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load_in_4bit=True # Enable 4-bit quantization for lower memory usage - requires bitsandbytes
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)
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# Prepare dataset
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SYSTEM_PROMPT = """
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Respond in the following format:
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<reasoning>
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...
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</reasoning>
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<answer>
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...
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</answer>
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"""
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text = tokenizer.apply_chat_template([
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{"role" : "system", "content" : SYSTEM_PROMPT},
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{"role" : "user", "content" : "Calculate pi."},
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], tokenize = False, add_generation_prompt = True)
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inputs = tokenizer(text, return_tensors="pt").to("cuda") # Move input tensor to GPU
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# Sampling parameters
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generation_config = GenerationConfig(
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temperature = 0.8,
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top_p = 0.95,
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max_new_tokens = 1024, # Equivalent to max_tokens in the original code, but for generation
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)
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# Inference
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with torch.inference_mode(): # Use inference mode for faster generation
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outputs = model.generate(**inputs, generation_config=generation_config)
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output = tokenizer.decode(outputs[0], skip_special_tokens=True)
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# Find the start of the actual response
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start_index = output.find("assistant")
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if start_index != -1:
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# Remove the initial part including "assistant"
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output = output[start_index + len("assistant"):].strip()
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print(output)
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```
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and the output is :
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```
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<reasoning>
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Pi is an irrational number, which means it cannot be precisely calculated using finite decimal or fractional notation. It is typically represented by the Greek letter π and its approximate value is 3.14159. However, for a more precise calculation, we can use mathematical algorithms like the Leibniz formula for π or the Gregory-Leibniz series.
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The Leibniz formula for π is:
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π = 4 * (1 - 1/3 + 1/5 - 1/7 + 1/9 - 1/11 + 1/13 - 1/15 +...)
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This series converges slowly, so many terms are needed for a good approximation. For instance, using 10 terms, the approximation would be:
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π ≈ 4 * (1 - 0.3333333333333333 + 0.1111111111111111 - 0.0344827586206897 + 0.0090040875518672 - 0.0025958422650073 + 0.0006929403729561 - 0.0001866279043531 + 0.0000499753694946 - 0.0000133386323746 + 0.0000035303398593 - 0.0000009009433996)
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π ≈ 3.141592653589793
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This is a rough approximation of π using 10 terms. For a more precise value, you can use more terms or employ other algorithms.
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</reasoning>
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<answer>
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π ≈ 3.141592653589793
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</answer>
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```
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---
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## Intended Use
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Granite-3.1-2B-Reasoning is designed for tasks requiring structured **reasoning**, including:
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- **Logical and analytical problem-solving**
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- **Text-based reasoning tasks**
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- **Mathematical and symbolic reasoning**
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- **Advanced instruction-following**
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---
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## License & Acknowledgments
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This model is released under the **Apache 2.0** license. It is fine-tuned from IBM’s **Granite 3.1-2B-Instruct** model. Special thanks to the **IBM Granite Team** for developing the base model.
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For more details, visit the [IBM Granite Documentation](https://huggingface.co/ibm-granite).
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---
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### Citation
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If you use this model in your research or applications, please cite:
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```
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@misc{ruslanmv2025granite,
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title={Fine-Tuning Granite-3.1 for Advanced Reasoning},
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author={Ruslan M.V.},
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year={2025},
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url={https://huggingface.co/ruslanmv/granite-3.1-2b-Reasoning}
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}
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```
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config.json
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{
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"_name_or_path": "ibm-granite/granite-3.1-2b-instruct",
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"architectures": [
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"tie_word_embeddings": true,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.48.2",
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"unsloth_version": "2025.2.5",
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"use_cache": true,
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"vocab_size": 49155
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}
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||||
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||||
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|
||||
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|
||||
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||||
"model.layers.8.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
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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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|
||||
"model.layers.9.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.norm.weight": "model-00002-of-00002.safetensors"
|
||||
}
|
||||
}
|
||||
29
special_tokens_map.json
Normal file
29
special_tokens_map.json
Normal file
@@ -0,0 +1,29 @@
|
||||
{
|
||||
"additional_special_tokens": [
|
||||
"<|start_of_role|>",
|
||||
"<|end_of_role|>",
|
||||
"<|tool_call|>"
|
||||
],
|
||||
"bos_token": {
|
||||
"content": "<|end_of_text|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"eos_token": {
|
||||
"content": "<|end_of_text|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"pad_token": "<|end_of_text|>",
|
||||
"unk_token": {
|
||||
"content": "<|end_of_text|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
}
|
||||
}
|
||||
244961
tokenizer.json
Normal file
244961
tokenizer.json
Normal file
File diff suppressed because it is too large
Load Diff
199
tokenizer_config.json
Normal file
199
tokenizer_config.json
Normal file
@@ -0,0 +1,199 @@
|
||||
{
|
||||
"add_bos_token": false,
|
||||
"add_prefix_space": false,
|
||||
"added_tokens_decoder": {
|
||||
"0": {
|
||||
"content": "<|end_of_text|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"1": {
|
||||
"content": "<fim_prefix>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"2": {
|
||||
"content": "<fim_middle>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"3": {
|
||||
"content": "<fim_suffix>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"4": {
|
||||
"content": "<fim_pad>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"5": {
|
||||
"content": "<filename>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"6": {
|
||||
"content": "<gh_stars>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"7": {
|
||||
"content": "<issue_start>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"8": {
|
||||
"content": "<issue_comment>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"9": {
|
||||
"content": "<issue_closed>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"10": {
|
||||
"content": "<jupyter_start>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"11": {
|
||||
"content": "<jupyter_text>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"12": {
|
||||
"content": "<jupyter_code>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"13": {
|
||||
"content": "<jupyter_output>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"14": {
|
||||
"content": "<empty_output>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"15": {
|
||||
"content": "<commit_before>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"16": {
|
||||
"content": "<commit_msg>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"17": {
|
||||
"content": "<commit_after>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"18": {
|
||||
"content": "<reponame>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"49152": {
|
||||
"content": "<|start_of_role|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"49153": {
|
||||
"content": "<|end_of_role|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"49154": {
|
||||
"content": "<|tool_call|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
}
|
||||
},
|
||||
"additional_special_tokens": [
|
||||
"<|start_of_role|>",
|
||||
"<|end_of_role|>",
|
||||
"<|tool_call|>"
|
||||
],
|
||||
"bos_token": "<|end_of_text|>",
|
||||
"chat_template": "{%- if messages[0]['role'] == 'system' %}\n {%- set system_message = messages[0]['content'] %}\n {%- set loop_messages = messages[1:] %}\n{%- else %}\n {%- set system_message = \"Knowledge Cutoff Date: April 2024.\nToday's Date: \" + strftime_now('%B %d, %Y') + \".\nYou are Granite, developed by IBM.\" %}\n {%- if tools and documents %}\n {%- set system_message = system_message + \" You are a helpful AI assistant with access to the following tools. When a tool is required to answer the user's query, respond with <|tool_call|> followed by a JSON list of tools used. If a tool does not exist in the provided list of tools, notify the user that you do not have the ability to fulfill the request.\n\nWrite the response to the user's input by strictly aligning with the facts in the provided documents. If the information needed to answer the question is not available in the documents, inform the user that the question cannot be answered based on the available data.\" %}\n {%- elif tools %}\n {%- set system_message = system_message + \" You are a helpful AI assistant with access to the following tools. When a tool is required to answer the user's query, respond with <|tool_call|> followed by a JSON list of tools used. If a tool does not exist in the provided list of tools, notify the user that you do not have the ability to fulfill the request.\" %}\n {%- elif documents %}\n {%- set system_message = system_message + \" Write the response to the user's input by strictly aligning with the facts in the provided documents. If the information needed to answer the question is not available in the documents, inform the user that the question cannot be answered based on the available data.\" %}\n {%- else %}\n {%- set system_message = system_message + \" You are a helpful AI assistant.\" %} \n {%- endif %}\n {%- if 'citations' in controls and documents %}\n {%- set system_message = system_message + '\n\nIn your response, use the symbols <co> and </co> to indicate when a fact comes from a document in the search result, e.g <co>0</co> for a fact from document 0. Afterwards, list all the citations with their corresponding documents in an ordered list.' %}\n {%- endif %}\n {%- if 'hallucinations' in controls and documents %}\n {%- set system_message = system_message + '\n\nFinally, after the response is written, include a numbered list of sentences from the response that are potentially hallucinated and not based in the documents.' %}\n {%- endif %}\n {%- set loop_messages = messages %}\n{%- endif %}\n{{- '<|start_of_role|>system<|end_of_role|>' + system_message + '<|end_of_text|>\n' }}\n{%- if tools %}\n {{- '<|start_of_role|>tools<|end_of_role|>' }}\n {{- tools | tojson(indent=4) }}\n {{- '<|end_of_text|>\n' }}\n{%- endif %}\n{%- if documents %}\n {{- '<|start_of_role|>documents<|end_of_role|>' }}\n {%- for document in documents %}\n {{- 'Document ' + loop.index0 | string + '\n' }}\n {{- document['text'] }}\n {%- if not loop.last %}\n {{- '\n\n'}}\n {%- endif%}\n {%- endfor %}\n {{- '<|end_of_text|>\n' }}\n{%- endif %}\n{%- for message in loop_messages %}\n {{- '<|start_of_role|>' + message['role'] + '<|end_of_role|>' + message['content'] + '<|end_of_text|>\n' }}\n {%- if loop.last and add_generation_prompt %}\n {{- '<|start_of_role|>assistant' }}\n {%- if controls %}\n {{- ' ' + controls | tojson()}}\n {%- endif %}\n {{- '<|end_of_role|>' }}\n {%- endif %}\n{%- endfor %}",
|
||||
"clean_up_tokenization_spaces": true,
|
||||
"eos_token": "<|end_of_text|>",
|
||||
"errors": "replace",
|
||||
"extra_special_tokens": {},
|
||||
"model_max_length": 131072,
|
||||
"pad_token": "<|end_of_text|>",
|
||||
"padding_side": "left",
|
||||
"tokenizer_class": "GPT2Tokenizer",
|
||||
"unk_token": "<|end_of_text|>",
|
||||
"vocab_size": 49152
|
||||
}
|
||||
1
vocab.json
Normal file
1
vocab.json
Normal file
File diff suppressed because one or more lines are too long
Reference in New Issue
Block a user