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Model: rubenroy/Zurich-7B-GCv2-5m
Source: Original Platform

.gitattributes

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README.md

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+---
+base_model: Qwen/Qwen2.5-7B-Instruct
+tags:
+- text-generation-inference
+- transformers
+- unsloth
+- qwen2
+- trl
+- gammacorpus
+- zurich
+- chat
+- conversational
+license: apache-2.0
+language:
+- en
+datasets:
+- rubenroy/GammaCorpus-v2-5m
+pipeline_tag: text-generation
+library_name: transformers
+---
+
+![Zunich Banner](https://cdn.ruben-roy.com/AI/Zurich/img/banner-7B-5m.png)
+
+# Zurich 7B GammaCorpus v2-5m 
+*A Qwen 2.5 model fine-tuned on the GammaCorpus dataset*
+
+## Overview
+Zurich 7B GammaCorpus v2-5m is a fine-tune of Alibaba's **Qwen 2.5 7B Instruct** model. Zurich is designed to outperform other models that have a similar size while also showcasing [GammaCorpus v2-5m](https://huggingface.co/datasets/rubenroy/GammaCorpus-v2-5m).
+
+## Model Details
+- **Base Model:** [Qwen/Qwen2.5-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct)
+- **Type:** Causal Language Models
+- **Architecture:** Transformers with RoPE, SwiGLU, RMSNorm, and Attention QKV bias
+- **Number of Parameters:** 7.61B
+- **Number of Paramaters (Non-Embedding):** 6.53B
+- **Number of Layers:** 28
+- **Number of Attention Heads (GQA):** 28 for Q and 4 for KV
+
+## Training Details
+
+Zurich-7B-GCv2-5m underwent fine-tuning with 1 A100 GPU for ~400 minutes and trained with the [Unsloth](https://unsloth.ai/) framework. Zurich-7B-GCv2-5m was trained for **60 Epochs**. 
+
+## Usage
+
+### Requirements
+
+We **strongly** recommend you use the latest version of the `transformers` package. You may install it via `pip` as follows:
+
+```
+pip install transformers
+```
+
+### Quickstart
+
+Here is a code snippet with `apply_chat_template` to show you how to load the tokenizer and model and how to generate contents;
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_name = "rubenroy/Zurich-7B-GCv2-5m"
+
+model = AutoModelForCausalLM.from_pretrained(
+    model_name,
+    torch_dtype="auto",
+    device_map="auto"
+)
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+
+prompt = "How tall is the Eiffel tower?"
+messages = [
+    {"role": "system", "content": "You are Zurich, an AI assistant built on the Qwen 2.5 7B model developed by Alibaba Cloud, and fine-tuned by Ruben Roy. You are a helpful assistant."},
+    {"role": "user", "content": prompt}
+]
+text = tokenizer.apply_chat_template(
+    messages,
+    tokenize=False,
+    add_generation_prompt=True
+)
+model_inputs = tokenizer([text], return_tensors="pt").to(model.device)
+
+generated_ids = model.generate(
+    **model_inputs,
+    max_new_tokens=512
+)
+generated_ids = [
+    output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
+]
+
+response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
+```
+
+## About GammaCorpus
+
+This model, and all Zurich models, are trained with GammaCorpus. GammaCorpus is a dataset on HuggingFace that is filled with structured and filtered multi-turn conversations.
+GammaCorpus has 4 version with different sizes in each. These are the following versions and sizes:
+
+### GammaCorpus v1
+- 10k UNFILTERED
+- 50k UNFILTERED
+- 70k UNFILTERED
+
+Here is a link to the GCv1 dataset collection:<br>
+https://huggingface.co/collections/rubenroy/gammacorpus-v1-67935e4e52a04215f15a7a60
+
+### GammaCorpus v2
+- 10k
+- 50k
+- 100k
+- 500k
+- 1m
+- **5m <-- This is the version of GammaCorpus v2 that the Zurich model you are using was trained on.**
+
+Here is a link to the GCv2 dataset collection:<br>
+https://huggingface.co/collections/rubenroy/gammacorpus-v2-67935e895e1259c404a579df
+
+### GammaCorpus CoT
+- Math 170k
+
+Here is a link to the GC-CoT dataset collection:<br>
+https://huggingface.co/collections/rubenroy/gammacorpus-cot-6795bbc950b62b1ced41d14f
+
+### GammaCorpus QA
+- Fact 450k
+
+Here is a link to the GC-QA dataset collection:<br>
+https://huggingface.co/collections/rubenroy/gammacorpus-qa-679857017bb3855234c1d8c7
+
+### The link to the full GammaCorpus dataset collection can be found [here](https://huggingface.co/collections/rubenroy/gammacorpus-67765abf607615a0eb6d61ac).
+
+## Known Limitations
+
+- **Bias:** We have tried our best to mitigate as much bias we can, but please be aware of the possibility that the model might generate some biased answers.
+
+## Additional Information
+
+### Licensing Information
+
+The model is released under the **[Apache 2.0 License](https://www.apache.org/licenses/LICENSE-2.0)**. Please refer to the license for usage rights and restrictions.

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config.json

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+  "_name_or_path": "rubenroy/Zurich-7B-GCv2-5m",
+  "architectures": [
+    "Qwen2ForCausalLM"
+  ],
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+  "max_window_layers": 28,
+  "model_type": "qwen2",
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+  "rms_norm_eps": 1e-06,
+  "rope_scaling": null,
+  "rope_theta": 1000000.0,
+  "sliding_window": null,
+  "tie_word_embeddings": false,
+  "torch_dtype": "float16",
+  "transformers_version": "4.47.1",
+  "unsloth_fixed": true,
+  "unsloth_version": "2025.1.7",
+  "use_cache": true,
+  "use_sliding_window": false,
+  "vocab_size": 152064
+}

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+  "transformers_version": "4.47.1"
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+}

special_tokens_map.json

@@ -0,0 +1,31 @@
+{
+  "additional_special_tokens": [
+    "<|im_start|>",
+    "<|im_end|>",
+    "<|object_ref_start|>",
+    "<|object_ref_end|>",
+    "<|box_start|>",
+    "<|box_end|>",
+    "<|quad_start|>",
+    "<|quad_end|>",
+    "<|vision_start|>",
+    "<|vision_end|>",
+    "<|vision_pad|>",
+    "<|image_pad|>",
+    "<|video_pad|>"
+  ],
+  "eos_token": {
+    "content": "<|im_end|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "<|PAD_TOKEN|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer.json

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:fab42efe8d17406525a9154b728cf9e957629a8ed7ce997770efdd71128c6a1a
+size 11422086

tokenizer_config.json

@@ -0,0 +1,217 @@
+{
+  "add_bos_token": false,
+  "add_prefix_space": false,
+  "added_tokens_decoder": {
+    "151643": {
+      "content": "<|endoftext|>",
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+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
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+      "single_word": false,
+      "special": true
+    },
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+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
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+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
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+      "rstrip": false,
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+      "special": true
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+    "151657": {
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+      "normalized": false,
+      "rstrip": false,
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+      "special": false
+    },
+    "151658": {
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+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
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+      "special": false
+    },
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+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151660": {
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+      "lstrip": false,
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+      "rstrip": false,
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+    },
+    "151661": {
+      "content": "<|fim_suffix|>",
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+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151662": {
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+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151663": {
+      "content": "<|repo_name|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151664": {
+      "content": "<|file_sep|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151665": {
+      "content": "<|PAD_TOKEN|>",
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+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "additional_special_tokens": [
+    "<|im_start|>",
+    "<|im_end|>",
+    "<|object_ref_start|>",
+    "<|object_ref_end|>",
+    "<|box_start|>",
+    "<|box_end|>",
+    "<|quad_start|>",
+    "<|quad_end|>",
+    "<|vision_start|>",
+    "<|vision_end|>",
+    "<|vision_pad|>",
+    "<|image_pad|>",
+    "<|video_pad|>"
+  ],
+  "bos_token": null,
+  "chat_template": "{%- if tools %}\n    {{- '<|im_start|>system\\n' }}\n    {%- if messages[0]['role'] == 'system' %}\n        {{- messages[0]['content'] }}\n    {%- else %}\n        {{- 'You are a helpful assistant named Zurich, a 7 billion parameter Large Language model. You were fine-tuned and trained by Ruben Roy. You have been trained with the GammaCorpus v2 dataset, a dataset filled with structured and filtered multi-turn conversations. This was also made by Ruben Roy.' }}\n    {%- endif %}\n    {{- \"\\n\\n# 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>\" }}\n    {%- for tool in tools %}\n        {{- \"\\n\" }}\n        {{- tool | tojson }}\n    {%- endfor %}\n    {{- \"\\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\" }}\n{%- else %}\n    {%- if messages[0]['role'] == 'system' %}\n        {{- '<|im_start|>system\\n' + messages[0]['content'] + '<|im_end|>\\n' }}\n    {%- else %}\n        {{- '<|im_start|>system\\nYou are a helpful assistant named Zurich, a 7 billion parameter Large Language model. You were fine-tuned and trained by Ruben Roy. You have been trained with the GammaCorpus v2 dataset, a dataset filled with structured and filtered multi-turn conversations. This was also made by Ruben Roy.<|im_end|>\\n' }}\n    {%- endif %}\n{%- endif %}\n{%- for message in messages %}\n    {%- if (message.role == \"user\") or (message.role == \"system\" and not loop.first) or (message.role == \"assistant\" and not message.tool_calls) %}\n        {{- '<|im_start|>' + message.role + '\\n' + message.content + '<|im_end|>' + '\\n' }}\n    {%- elif message.role == \"assistant\" %}\n        {{- '<|im_start|>' + message.role }}\n        {%- if message.content %}\n            {{- '\\n' + message.content }}\n        {%- endif %}\n        {%- for tool_call in message.tool_calls %}\n            {%- if tool_call.function is defined %}\n                {%- set tool_call = tool_call.function %}\n            {%- endif %}\n            {{- '\\n<tool_call>\\n{\"name\": \"' }}\n            {{- tool_call.name }}\n            {{- '\", \"arguments\": ' }}\n            {{- tool_call.arguments | tojson }}\n            {{- '}\\n</tool_call>' }}\n        {%- endfor %}\n        {{- '<|im_end|>\\n' }}\n    {%- elif message.role == \"tool\" %}\n        {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != \"tool\") %}\n            {{- '<|im_start|>user' }}\n        {%- endif %}\n        {{- '\\n<tool_response>\\n' }}\n        {{- message.content }}\n        {{- '\\n</tool_response>' }}\n        {%- if loop.last or (messages[loop.index0 + 1].role != \"tool\") %}\n            {{- '<|im_end|>\\n' }}\n        {%- endif %}\n    {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n    {{- '<|im_start|>assistant\\n' }}\n{%- endif %}\n",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|im_end|>",
+  "errors": "replace",
+  "extra_special_tokens": {},
+  "model_max_length": 32768,
+  "pad_token": "<|PAD_TOKEN|>",
+  "padding_side": "left",
+  "split_special_tokens": false,
+  "tokenizer_class": "Qwen2Tokenizer",
+  "unk_token": null
+}