初始化项目，由ModelHub XC社区提供模型

Model: 979-6/Nidum-Gemma-2B-Uncensored
Source: Original Platform

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README.md

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+---
+license: gemma
+tags:
+- legal
+- chemistry
+- medical
+- text-generation-inference
+- art
+- finance
+- uncensored
+pipeline_tag: text-generation
+---
+# Nidum-Limitless-Gemma-2B LLM
+
+Welcome to the repository for Nidum-Limitless-Gemma-2B, an advanced language model that provides unrestricted and versatile responses across a wide range of topics. Unlike conventional models, Nidum-Limitless-Gemma-2B is designed to handle any type of question and deliver comprehensive answers without content restrictions.
+
+## Key Features:
+- **Unrestricted Responses:** Address any query with detailed, unrestricted responses, providing a broad spectrum of information and insights.
+- **Versatility:** Capable of engaging with a diverse range of topics, from complex scientific questions to casual conversation.
+- **Advanced Understanding:** Leverages a vast knowledge base to deliver contextually relevant and accurate outputs across various domains.
+- **Customizability:** Adaptable to specific user needs and preferences for different types of interactions.
+
+## Use Cases:
+- Open-Ended Q&A
+- Creative Writing and Ideation
+- Research Assistance
+- Educational and Informational Queries
+- Casual Conversations and Entertainment
+
+## How to Use:
+
+To get started with Nidum-Limitless-Gemma-2B, you can use the following sample code for testing:
+
+```python
+import torch
+from transformers import pipeline
+
+pipe = pipeline(
+    "text-generation",
+    model="nidum/Nidum-Limitless-Gemma-2B",
+    model_kwargs={"torch_dtype": torch.bfloat16},
+    device="cuda",  # replace with "mps" to run on a Mac device
+)
+
+messages = [
+    {"role": "user", "content": "who are you"},
+]
+
+outputs = pipe(messages, max_new_tokens=256)
+assistant_response = outputs[0]["generated_text"][-1]["content"].strip()
+print(assistant_response)
+```
+
+## Release Date:
+Nidum-Limitless-Gemma-2B is now officially available. Explore its capabilities and experience the freedom of unrestricted responses.
+
+## Contributing:
+We welcome contributions to enhance the model or expand its functionalities. Details on how to contribute will be available in the coming updates.
+
+## Quantized Model Versions
+
+To accommodate different hardware configurations and performance needs, Nidum-Limitless-Gemma-2B-GGUF is available in multiple quantized versions:
+
+| Model Version                                  | Description                                           |
+|------------------------------------------------|-------------------------------------------------------|
+| **Nidum-Limitless-Gemma-2B-Q2_K.gguf**         | Optimized for minimal memory usage with lower precision. Suitable for resource-constrained environments. |
+| **Nidum-Limitless-Gemma-2B-Q4_K_M.gguf**       | Balances performance and precision, offering faster inference with moderate memory usage. |
+| **Nidum-Limitless-Gemma-2B-Q8_0.gguf**         | Provides higher precision with increased memory usage, suitable for tasks requiring more accuracy. |
+| **Nidum-Limitless-Gemma-2B-F16.gguf**          | Full 16-bit floating point precision for maximum accuracy, ideal for high-end GPUs. |
+
+It is available here: https://huggingface.co/nidum/Nidum-Limitless-Gemma-2B-GGUF
+
+## Contact:
+For any inquiries or further information, please contact us at **info@nidum.ai**.
+
+---
+
+Dive into limitless possibilities with Nidum-Limitless-Gemma-2B!
+
+Special Thanks to @cognitivecomputations for inspiring us and scouting the best datasets that we could round up to make a rockstar model for you
+---

config.json

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+{
+  "_name_or_path": "saves/Gemma-2B-Chat/full/train_2024-08-04-05-53-43",
+  "architectures": [
+    "GemmaForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 2,
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+  "hidden_act": "gelu",
+  "hidden_activation": "gelu_pytorch_tanh",
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+  "initializer_range": 0.02,
+  "intermediate_size": 16384,
+  "max_position_embeddings": 8192,
+  "model_type": "gemma",
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+  "num_hidden_layers": 18,
+  "num_key_value_heads": 1,
+  "pad_token_id": 0,
+  "rms_norm_eps": 1e-06,
+  "rope_scaling": null,
+  "rope_theta": 10000.0,
+  "torch_dtype": "float32",
+  "transformers_version": "4.43.3",
+  "use_cache": true,
+  "vocab_size": 256000
+}

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+  "bos_token_id": 2,
+  "eos_token_id": 1,
+  "pad_token_id": 0,
+  "transformers_version": "4.43.3"
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special_tokens_map.json

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