commit 1581a65ba239f45661f1b41f21fceb52781948bf
Author: ModelHub XC <noreply@modelhub.org.cn>
Date:   Sat Jul 25 18:13:06 2026 +0800

    初始化项目，由ModelHub XC社区提供模型
    
    Model: prithivMLmods/Blaze.1-27B-Reflection
    Source: Original Platform

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diff --git a/README.md b/README.md
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+---
+license: gemma
+language:
+- en
+base_model:
+- google/gemma-2-27b-it
+pipeline_tag: text-generation
+library_name: transformers
+tags:
+- text-generation-inference
+---
+![8.png](https://cdn-uploads.huggingface.co/production/uploads/65bb837dbfb878f46c77de4c/vebaBsL6MsLveGCH3y1ig.png)
+
+Blaze.1-27B-Reflection is a Gemma 2-based 27B parameter model. Gemma is a family of lightweight, state-of-the-art open models from Google, built using the same research and technology behind the Gemini models. These models are text-to-text, decoder-only large language models available in English, with open weights for both pre-trained and instruction-tuned variants. Gemma models are well-suited for a variety of text generation tasks, including question answering, summarization, and reasoning. Blaze.1-27B-Reflection is fine-tuned on self-reflection and behavioral data, using synthetic datasets for long-chain-of-thought reasoning from models such as DeepSeek and QwQ.
+
+# **Quickstart Chat Template**
+
+Below we share some code snippets on how to get quickly started with running the model. First, install the Transformers library with:
+```sh
+pip install -U transformers
+```
+
+Then, copy the snippet from the section that is relevant for your usecase.
+
+# **Running with the `pipeline` API**
+
+```python
+import torch
+from transformers import pipeline
+
+pipe = pipeline(
+    "text-generation",
+    model="prithivMLmods/Blaze.1-27B-Reflection",
+    model_kwargs={"torch_dtype": torch.bfloat16},
+    device="cuda",  # replace with "mps" to run on a Mac device
+)
+
+messages = [
+    {"role": "user", "content": "Who are you? Please, answer in pirate-speak."},
+]
+
+outputs = pipe(messages, max_new_tokens=256)
+assistant_response = outputs[0]["generated_text"][-1]["content"].strip()
+print(assistant_response)
+# Ahoy, matey! I be Gemma, a digital scallywag, a language-slingin' parrot of the digital seas. I be here to help ye with yer wordy woes, answer yer questions, and spin ye yarns of the digital world.  So, what be yer pleasure, eh? 🦜
+```
+
+# **Running the model on a single / multi GPU**
+
+```python
+# pip install accelerate
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
+
+tokenizer = AutoTokenizer.from_pretrained("prithivMLmods/Blaze.1-27B-Reflection")
+model = AutoModelForCausalLM.from_pretrained(
+    "prithivMLmods/Blaze.1-27B-Reflection",
+    device_map="auto",
+    torch_dtype=torch.bfloat16,
+)
+
+input_text = "Write me a poem about Machine Learning."
+input_ids = tokenizer(input_text, return_tensors="pt").to("cuda")
+
+outputs = model.generate(**input_ids, max_new_tokens=32)
+print(tokenizer.decode(outputs[0]))
+```
+
+You can ensure the correct chat template is applied by using `tokenizer.apply_chat_template` as follows:
+```python
+messages = [
+    {"role": "user", "content": "Write me a poem about Machine Learning."},
+]
+input_ids = tokenizer.apply_chat_template(messages, return_tensors="pt", return_dict=True).to("cuda")
+
+outputs = model.generate(**input_ids, max_new_tokens=256)
+print(tokenizer.decode(outputs[0]))
+```
+
+<a name="precisions"></a>
+
+# **Running the model on a GPU using different precisions**
+
+The native weights of this model were exported in `bfloat16` precision.
+
+You can also use `float32` if you skip the dtype, but no precision increase will occur (model weights will just be upcasted to `float32`). See examples below.
+
+* _Upcasting to `torch.float32`_
+
+```python
+# pip install accelerate
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+tokenizer = AutoTokenizer.from_pretrained("prithivMLmods/Blaze.1-27B-Reflection")
+model = AutoModelForCausalLM.from_pretrained(
+    "prithivMLmods/Blaze.1-27B-Reflection",
+    device_map="auto",
+)
+
+input_text = "Write me a poem about Machine Learning."
+input_ids = tokenizer(input_text, return_tensors="pt").to("cuda")
+
+outputs = model.generate(**input_ids, max_new_tokens=32)
+print(tokenizer.decode(outputs[0]))
+```
+
+# **Intended Use**  
+Blaze.1-27B-Reflection is designed for advanced reasoning tasks that require long-chain-of-thought processing, self-reflection, and behavioral analysis. Its primary applications include:  
+
+1. **Question Answering**: The model excels in providing detailed, step-by-step answers to complex queries.  
+2. **Summarization**: It can generate concise summaries of large text inputs, maintaining key information and logical flow.  
+3. **Reasoning and Decision Support**: With its fine-tuning on self-reflection data, it can assist in tasks that require thoughtful analysis, such as legal reasoning, policy development, and strategic planning.  
+4. **Conversational AI**: Due to its instruction-tuned nature, it performs well in interactive dialogue systems, offering coherent and context-aware responses.  
+5. **Creative Writing**: The model can be employed in generating high-quality content for creative tasks, including storytelling and content ideation.
+
+# **Limitations**  
+1. **Language and Domain Constraints**: While the model is effective in English, it may perform poorly with non-English inputs or domain-specific jargon outside its training scope.  
+2. **Context Retention Issues**: In very long conversations or documents, the model may lose track of earlier context, leading to incomplete or off-topic responses.  
+3. **Over-reliance on Synthetic Data**: Since Blaze.1-27B-Reflection is fine-tuned on synthetic datasets, it may exhibit biases or inconsistencies when faced with real-world, nuanced scenarios.  
+4. **Circular Reasoning**: The model may occasionally enter recursive reasoning loops, generating verbose responses without reaching a clear conclusion.  
+5. **Computational Demand**: As a 27B parameter model, it requires substantial computational resources for both inference and fine-tuning, which may limit its accessibility for users with limited hardware.  
+6. **Hallucinations**: Like most large language models, it may confidently generate incorrect information, especially when asked about facts or events outside its training data.
diff --git a/config.json b/config.json
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+{
+  "_name_or_path": "google/gemma-2-27b-it",
+  "architectures": [
+    "Gemma2ForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "attn_logit_softcapping": 50.0,
+  "bos_token_id": 2,
+  "cache_implementation": "hybrid",
+  "eos_token_id": 1,
+  "final_logit_softcapping": 30.0,
+  "head_dim": 128,
+  "hidden_act": "gelu_pytorch_tanh",
+  "hidden_activation": "gelu_pytorch_tanh",
+  "hidden_size": 4608,
+  "initializer_range": 0.02,
+  "intermediate_size": 36864,
+  "max_position_embeddings": 8192,
+  "model_type": "gemma2",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 46,
+  "num_key_value_heads": 16,
+  "pad_token_id": 0,
+  "query_pre_attn_scalar": 144,
+  "rms_norm_eps": 1e-06,
+  "rope_scaling": null,
+  "rope_theta": 10000.0,
+  "sliding_window": 4096,
+  "sliding_window_size": 4096,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.47.1",
+  "use_cache": true,
+  "vocab_size": 256000
+}
diff --git a/configuration.json b/configuration.json
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--- /dev/null
+++ b/configuration.json
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+{"framework": "pytorch", "task": "text-generation", "allow_remote": true}
\ No newline at end of file
diff --git a/generation_config.json b/generation_config.json
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--- /dev/null
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+{
+  "_from_model_config": true,
+  "bos_token_id": 2,
+  "cache_implementation": "hybrid",
+  "eos_token_id": 1,
+  "max_length": 8192,
+  "pad_token_id": 0,
+  "transformers_version": "4.47.1"
+}
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+    "181": {
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+      "special": false
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+    "182": {
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+      "rstrip": false,
+      "single_word": false,
+      "special": false
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+    "183": {
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+      "special": false
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+    "186": {
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+      "rstrip": false,
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+    "198": {
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+      "rstrip": false,
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+    },
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+      "rstrip": false,
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+    "205": {
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+      "rstrip": false,
+      "single_word": false,
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+    },
+    "213": {
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+      "rstrip": false,
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+    },
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+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "255968": {
+      "content": "[toxicity=0]",
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+      "special": false
+    },
+    "255969": {
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+    },
+    "255970": {
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+    },
+    "255971": {
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+    },
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+    },
+    "255984": {
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+      "lstrip": false,
+      "normalized": false,
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+    },
+    "255985": {
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+      "normalized": false,
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+    },
+    "255986": {
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+    "255988": {
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+    },
+    "255989": {
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+    },
+    "255990": {
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+    },
+    "255992": {
+      "content": "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
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+    },
+    "255993": {
+      "content": "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "255994": {
+      "content": "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "255995": {
+      "content": "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "255996": {
+      "content": "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "255997": {
+      "content": "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "255998": {
+      "content": "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "255999": {
+      "content": "<unused99>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    }
+  },
+  "additional_special_tokens": [
+    "<start_of_turn>",
+    "<end_of_turn>"
+  ],
+  "bos_token": "<bos>",
+  "chat_template": "{{ bos_token }}{% if messages[0]['role'] == 'system' %}{{ raise_exception('System role not supported') }}{% endif %}{% for message in messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% if (message['role'] == 'assistant') %}{% set role = 'model' %}{% else %}{% set role = message['role'] %}{% endif %}{{ '<start_of_turn>' + role + '\n' + message['content'] | trim + '<end_of_turn>\n' }}{% endfor %}{% if add_generation_prompt %}{{'<start_of_turn>model\n'}}{% endif %}",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<eos>",
+  "extra_special_tokens": {},
+  "model_max_length": 8192,
+  "pad_token": "<pad>",
+  "padding_side": "left",
+  "sp_model_kwargs": {},
+  "spaces_between_special_tokens": false,
+  "tokenizer_class": "GemmaTokenizer",
+  "unk_token": "<unk>",
+  "use_default_system_prompt": false
+}