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Model: AliMaatouk/Llama-3.2-3B-Tele Source: Original Platform
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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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pipeline_tag: text-generation
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tags:
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- nlp
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---
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# Llama-3.2-3B-Tele Model Card
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## Model Summary
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The language model Llama-3.2-3B-Tele is a Transformer with **3 billion** parameters, specialized in telecommunications. It is based on Meta [Llama-3.2-3B](https://huggingface.co/meta-llama/Llama-3.2-3B) and was continutally pretrained on [Tele-Data](https://huggingface.co/datasets/AliMaatouk/Tele-Data), a large-scale dataset of approximately 2.5 billion tokens of telecommunications material, including articles, standards, and general web content related to the telecommunications domain.
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When assessed against telecommunications benchmarks such as [Tele-Eval](https://huggingface.co/datasets/AliMaatouk/Tele-Eval), Llama-3.2-3B-Tele outperforms [Llama-3.2-3B](https://huggingface.co/meta-llama/Llama-3.2-3B) by several percentage points. Additionally, Llama-3.2-3B-Tele matches [Llama-3.2-3B](https://huggingface.co/meta-llama/Llama-3.2-3B) across benchmarks related to common sense, language understanding, and logical reasoning. Thus, this adaptation was achieved with minimal compromise in performance on the original version.
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### Context Length
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The model was trained on a context length of 8192 tokens.
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## Usage
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Llama-3.2-3B-Tele is a base model best suited for fine-tuning on applications related to telecommunications. It has not been fine-tuned to follow instructions and operates solely within a text completion framework. An example of this completion can be found below:
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```markdown
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Prompt: Shannon capacity is
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Model: the maximum rate at which information can be transmitted over a communication channel. It is named after Claude Shannon, who introduced the concept in his 1948 paper "A Mathematical Theory of Communication". Shannon's work was a major breakthrough in the field of information theory, and his capacity formula is one of the most important results in the field.
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```
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The instruct version of this model can be found by following the link [Llama-3.2-3B-Tele-it](https://huggingface.co/AliMaatouk/Llama-3.2-3B-Tele-it).
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## Sample Code
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Below we share some code snippets on how to get quickly started with running the model. First, make sure to `pip install transformers`, then copy the snippet corresponding to your hardware and adapt it to your usecase.
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#### Running the model on a CPU
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```python
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from transformers import AutoTokenizer, AutoModelForCausalLM
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model = AutoModelForCausalLM.from_pretrained("AliMaatouk/Llama-3.2-3B-Tele", torch_dtype="auto")
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tokenizer = AutoTokenizer.from_pretrained("AliMaatouk/Llama-3.2-3B-Tele")
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prompt = "Shannon capacity is"
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input_ids = tokenizer(prompt, return_tensors="pt")
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outputs = model.generate(**input_ids, max_new_tokens=100)
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generated_tokens = outputs[0, len(input_ids['input_ids'][0]):]
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response = tokenizer.decode(generated_tokens, skip_special_tokens=True)
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print(response)
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```
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#### Running the model on a single / multi GPU
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```python
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import torch
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from transformers import AutoModelForCausalLM, AutoTokenizer
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model = AutoModelForCausalLM.from_pretrained("AliMaatouk/Llama-3.2-3B-Tele", torch_dtype="auto", device_map="auto")
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tokenizer = AutoTokenizer.from_pretrained("AliMaatouk/Llama-3.2-3B-Tele")
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prompt = "Shannon capacity is"
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input_ids = tokenizer(prompt, return_tensors="pt").to("cuda")
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outputs = model.generate(**input_ids, max_new_tokens=100)
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generated_tokens = outputs[0, len(input_ids['input_ids'][0]):]
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response = tokenizer.decode(generated_tokens, skip_special_tokens=True)
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print(response)
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```
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## Citation
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You can find the paper with all details about the model at https://arxiv.org/abs/2409.05314. Please cite it as follows:
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```bib
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@misc{maatouk2024telellmsseriesspecializedlarge,
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title={Tele-LLMs: A Series of Specialized Large Language Models for Telecommunications},
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author={Ali Maatouk and Kenny Chirino Ampudia and Rex Ying and Leandros Tassiulas},
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year={2024},
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eprint={2409.05314},
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archivePrefix={arXiv},
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primaryClass={cs.IT},
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url={https://arxiv.org/abs/2409.05314},
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}
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```
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config.json
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||||
23
special_tokens_map.json
Normal file
23
special_tokens_map.json
Normal file
@@ -0,0 +1,23 @@
|
||||
{
|
||||
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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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||||
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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.
2062
tokenizer_config.json
Normal file
2062
tokenizer_config.json
Normal file
File diff suppressed because it is too large
Load Diff
Reference in New Issue
Block a user