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Model: farbodtavakkoli/OTel-LLM-14B-IT
Source: Original Platform

.gitattributes

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README.md

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+---
+license: apache-2.0
+language:
+- en
+base_model:
+- Qwen/Qwen3-14B
+tags:
+- telecom
+- telecommunications
+- gsma
+- fine-tuned
+pipeline_tag: text-generation
+---
+
+# OTel-LLM-14B-IT
+
+**OTel-LLM-14B-IT** is a telecom-specialized language model fine-tuned on telecommunications domain data. It is part of the [OTel Family of Models](https://huggingface.co/collections/farbodtavakkoli/otel-llm), an open-source initiative to build industry-standard AI models for the global telecommunications sector.
+
+## Model Details
+
+| Attribute | Value |
+|-----------|-------|
+| **Base Model** | [Qwen/Qwen3-14B](https://huggingface.co/Qwen/Qwen3-14B) |
+| **Parameters** | 14B |
+| **Training Method** | Full parameter fine-tuning |
+| **Language** | English |
+| **License** | Apache 2.0 |
+
+## Training Data
+
+The model was trained on telecom-focused data curated by 100+ domain experts. Each source class was contributed by a specific institutional partner:
+
+| Source | Contributor |
+|---|---|
+| arXiv telecom papers, 3GPP standards, telecom Wikipedia, telecom Common Crawl | Yale University |
+| GSMA Permanent Reference Documents, Discover portal | GSMA |
+| IETF RFC series | NetoAI |
+| Industry whitepapers | Khalifa University |
+| O-RAN specifications (working groups 1, 2, 4, 5, 6, 7, 8, 9, 10) | University of Leeds |
+| O-RAN documents across working groups | The University of Texas at Dallas |
+
+Released datasets: [OTel-LLM](https://huggingface.co/datasets/farbodtavakkoli/OTel-LLM), [OTel-Embedding](https://huggingface.co/datasets/farbodtavakkoli/OTel-Embedding), [OTel-Reranker](https://huggingface.co/datasets/farbodtavakkoli/OTel-Reranker), [OTel-Safety](https://huggingface.co/datasets/farbodtavakkoli/OTel-Safety).
+
+## Intended Use
+ 
+The OTel model family is designed to power end-to-end Retrieval-Augmented Generation (RAG) pipelines for telecommunications. The three model types serve complementary roles:
+ 
+1. **Embedding** — Retrieve relevant chunks from telecom specifications, standards, and documentation.
+2. **Reranker** — Re-score and prioritize the retrieved chunks for relevance.
+3. **LLM** — Generate accurate responses grounded in the retrieved context.
+ 
+Users can deploy the full pipeline or use individual models independently based on their needs.
+ 
+**Note:** The LLMs include abstention training — if the model does not receive sufficient context, it will decline to answer rather than hallucinate. This means the models are optimized for context-grounded generation, not open-ended question answering.
+
+## Related Models
+
+### Language Models
+- [OTel LLM Collection](https://huggingface.co/collections/farbodtavakkoli/otel-llm)
+
+### Embedding Models
+- [OTel Embedding Collection](https://huggingface.co/collections/farbodtavakkoli/otel-embedding)
+
+### Reranker Models
+- [OTel Reranker Collection](https://huggingface.co/collections/farbodtavakkoli/otel-reranker)
+
+## Related Datasets
+
+- [OTel-Embedding](https://huggingface.co/datasets/farbodtavakkoli/OTel-Embedding)
+- [OTel-Safety](https://huggingface.co/datasets/farbodtavakkoli/OTel-Safety)
+- [OTel-LLM](https://huggingface.co/datasets/farbodtavakkoli/OTel-LLM)
+- [OTel-Reranker](https://huggingface.co/datasets/farbodtavakkoli/OTel-Reranker)
+
+## Training Infrastructure
+
+- **Framework**: ScalarLM (GPU-agnostic)
+- **Compute**: AMD and NVIDIA GPUs.
+
+## Project Resources
+
+- **Project page:** https://huggingface.co/farbodtavakkoli
+- **Code:** https://github.com/farbodtavakkoli/OTel
+- **Media coverage list:** https://github.com/farbodtavakkoli/OTel/blob/main/docs/media_coverage.md
+
+## Citation
+
+
+```bibtex
+@misc{otel_models_2026,
+  title  = {OTel: Open Telco AI Datasets, Benchmarks, and Models},
+  author = {Tavakkoli, Farbod and others},
+  year   = {2026},
+  note   = {Open Telco (OTel) model release},
+  url    = {https://huggingface.co/farbodtavakkoli}
+}
+```
+
+## Contact
+
+If you have any technical questions, please feel free to reach out to farbod.tavakkoli@att.com or farbodtavakoli@gmail.com

added_tokens.json

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+  "</tool_call>": 151658,
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+{%- if tools %}
+    {{- '<|im_start|>system\n' }}
+    {%- if messages[0].role == 'system' %}
+        {{- messages[0].content + '\n\n' }}
+    {%- endif %}
+    {{- "# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
+    {%- for tool in tools %}
+        {{- "\n" }}
+        {{- tool | tojson }}
+    {%- endfor %}
+    {{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
+{%- else %}
+    {%- if messages[0].role == 'system' %}
+        {{- '<|im_start|>system\n' + messages[0].content + '<|im_end|>\n' }}
+    {%- endif %}
+{%- endif %}
+{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
+{%- for message in messages[::-1] %}
+    {%- set index = (messages|length - 1) - loop.index0 %}
+    {%- if ns.multi_step_tool and message.role == "user" and message.content is string and not(message.content.startswith('<tool_response>') and message.content.endswith('</tool_response>')) %}
+        {%- set ns.multi_step_tool = false %}
+        {%- set ns.last_query_index = index %}
+    {%- endif %}
+{%- endfor %}
+{%- for message in messages %}
+    {%- if message.content is string %}
+        {%- set content = message.content %}
+    {%- else %}
+        {%- set content = '' %}
+    {%- endif %}
+    {%- if (message.role == "user") or (message.role == "system" and not loop.first) %}
+        {{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
+    {%- elif message.role == "assistant" %}
+        {%- set reasoning_content = '' %}
+        {%- if message.reasoning_content is string %}
+            {%- set reasoning_content = message.reasoning_content %}
+        {%- else %}
+            {%- if '</think>' in content %}
+                {%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
+                {%- set content = content.split('</think>')[-1].lstrip('\n') %}
+            {%- endif %}
+        {%- endif %}
+        {%- if loop.index0 > ns.last_query_index %}
+            {%- if loop.last or (not loop.last and reasoning_content) %}
+                {{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content.strip('\n') + '\n</think>\n\n' + content.lstrip('\n') }}
+            {%- else %}
+                {{- '<|im_start|>' + message.role + '\n' + content }}
+            {%- endif %}
+        {%- else %}
+            {{- '<|im_start|>' + message.role + '\n' + content }}
+        {%- endif %}
+        {%- if message.tool_calls %}
+            {%- for tool_call in message.tool_calls %}
+                {%- if (loop.first and content) or (not loop.first) %}
+                    {{- '\n' }}
+                {%- endif %}
+                {%- if tool_call.function %}
+                    {%- set tool_call = tool_call.function %}
+                {%- endif %}
+                {{- '<tool_call>\n{"name": "' }}
+                {{- tool_call.name }}
+                {{- '", "arguments": ' }}
+                {%- if tool_call.arguments is string %}
+                    {{- tool_call.arguments }}
+                {%- else %}
+                    {{- tool_call.arguments | tojson }}
+                {%- endif %}
+                {{- '}\n</tool_call>' }}
+            {%- endfor %}
+        {%- endif %}
+        {{- '<|im_end|>\n' }}
+    {%- elif message.role == "tool" %}
+        {%- if loop.first or (messages[loop.index0 - 1].role != "tool") %}
+            {{- '<|im_start|>user' }}
+        {%- endif %}
+        {{- '\n<tool_response>\n' }}
+        {{- content }}
+        {{- '\n</tool_response>' }}
+        {%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
+            {{- '<|im_end|>\n' }}
+        {%- endif %}
+    {%- endif %}
+{%- endfor %}
+{%- if add_generation_prompt %}
+    {{- '<|im_start|>assistant\n' }}
+    {%- if enable_thinking is defined and enable_thinking is false %}
+        {{- '<think>\n\n</think>\n\n' }}
+    {%- endif %}
+{%- endif %}

config.json

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+{
+  "architectures": [
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+  ],
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+  "attention_dropout": 0.0,
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+  "layer_types": [
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+  "max_position_embeddings": 40960,
+  "max_window_layers": 40,
+  "model_type": "qwen3",
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+  "num_hidden_layers": 40,
+  "num_key_value_heads": 8,
+  "pad_token_id": 151643,
+  "rms_norm_eps": 1e-06,
+  "rope_scaling": null,
+  "rope_theta": 1000000,
+  "sliding_window": null,
+  "tie_word_embeddings": false,
+  "transformers_version": "4.57.6",
+  "use_cache": false,
+  "use_sliding_window": false,
+  "vocab_size": 151936
+}

generation_config.json

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+  "top_k": 20,
+  "top_p": 0.95,
+  "transformers_version": "4.57.6"
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