Update README.md

README.md

@@ -1,9 +1,54 @@
+# SmolLM2 1.7B
+
+SmolLM2 was trained on 11 trillion tokens and demonstrates significant advances over other small models, particularly in instruction following, knowledge, reasoning, and mathematics.  
+
+**Model Intention:** SmolLM2 is capable of solving a wide range of tasks while being lightweight enough to run on-device  
+
+**Model URL:** [https://huggingface.co/flyingfishinwater/good_and_small_models/resolve/main/smollm2-1.7b-instruct-q4_k_m.gguf?download=true](https://huggingface.co/flyingfishinwater/good_and_small_models/resolve/main/smollm2-1.7b-instruct-q4_k_m.gguf?download=true)  
+
+**Model Info URL:** [https://huggingface.co/HuggingFaceTB/SmolLM2-1.7B-Instruct](https://huggingface.co/HuggingFaceTB/SmolLM2-1.7B-Instruct)  
+
+**Model License:** [License Info](https://choosealicense.com/licenses/apache-2.0/)  
+
+**Model Description:** SmolLM2 was trained on 11 trillion tokens and demonstrates significant advances over other small models, particularly in instruction following, knowledge, reasoning, and mathematics.  
+
+**Developer:** [https://huggingface.co/HuggingFaceTB](https://huggingface.co/HuggingFaceTB)  
+
+**Update Date:** 2024-11-02  
+
+**File Size:** 1060 MB  
+
+**Context Length:** 8192 tokens  
+
+**Prompt Format:** 
+
+```
+<|im_start|>system
+{{system}}<|im_end|>
+<|im_start|>user
+{{prompt}}<|im_end|>
+<|im_start|>assistant
+
+```
+
+**Template Name:** chatml  
+
+**Add BOS Token:** Yes  
+
+**Add EOS Token:** No  
+
+**Parse Special Tokens:** Yes  
+
+
+---
+
 # Reader-LM 1.5B
+
 Jina Reader-LM is a model that convert HTML content to Markdown content, which is useful for content conversion tasks. The model is trained on a curated collection of HTML content and its corresponding Markdown content.  
 
 **Model Intention:** Jina Reader-LM is used to convert HTML content to Markdown content, which is useful for content conversion tasks  
 
-**Model URL:** [https://huggingface.co/flyingfishinwater/good_and_small_models/resolve/main/reader-lm-1.5b-Q4_K_M.gguf?download=true](https://huggingface.co/flyingfishinwater/good_and_small_models/resolve/main/reader-lm-1.5b-Q4_K_M.gguf?download=true)  
+**Model URL:** [https://huggingface.co/flyingfishinwater/good_and_small_models/resolve/main/smollm2-1.7b-instruct-q4_k_m.gguf.gguf?download=true](https://huggingface.co/flyingfishinwater/good_and_small_models/resolve/main/smollm2-1.7b-instruct-q4_k_m.gguf.gguf?download=true)  
 
 **Model Info URL:** [https://huggingface.co/jinaai/reader-lm-1.5b](https://huggingface.co/jinaai/reader-lm-1.5b)  
 
@@ -20,6 +65,7 @@ Jina Reader-LM is a model that convert HTML content to Markdown content, which i
 **Context Length:** 8192 tokens  
 
 **Prompt Format:** 
+
 ```
 <|im_start|>system
 {{system}}<|im_end|>
@@ -27,7 +73,7 @@ Jina Reader-LM is a model that convert HTML content to Markdown content, which i
 {{prompt}}<|im_end|>
 <|im_start|>assistant
 
-``` 
+```
 
 **Template Name:** chatml  
 
@@ -41,6 +87,7 @@ Jina Reader-LM is a model that convert HTML content to Markdown content, which i
 ---
 
 # WhiteRabbitNeo V2(Llama3.1)
+
 It identifies cybersecurity risks such as open ports, outdated software, default credentials, misconfigurations, injection flaws, unencrypted services, known vulnerabilities, CSRF, insecure object references, broken authentication, sensitive data exposure, API vulnerabilities, DoS risks, and buffer overflows, enabling threat detection and mitigation.  
 
 **Model Intention:** It is a 8B model that can be used for defensive cybersecurity.  
@@ -62,13 +109,14 @@ It identifies cybersecurity risks such as open ports, outdated software, default
 **Context Length:** 8192 tokens  
 
 **Prompt Format:** 
+
 ```
 <|begin_of_text|><|start_header_id|>system<|end_header_id|>
 
 {{system}}<|eot_id|><|start_header_id|>user<|end_header_id|>
 
 
-``` 
+```
 
 **Template Name:** chatml  
 
@@ -82,6 +130,7 @@ It identifies cybersecurity risks such as open ports, outdated software, default
 ---
 
 # Dolphin 2.9.4 Gemma2 2b
+
 Dolphin-2.9.4 has a variety of instruction following, conversational, and coding skills. It also has agentic abilities and supports function calling. It is especially trained to obey the system prompt, and follow instructions in many languages.  Dolphin is uncensored. We have filtered the dataset to remove alignment and bias. This makes the model more compliant.  
 
 **Model Intention:** It has a variety of instruction following, conversational, and coding skills. It also has agentic abilities and supports function calling.  
@@ -103,6 +152,7 @@ Dolphin-2.9.4 has a variety of instruction following, conversational, and coding
 **Context Length:** 4096 tokens  
 
 **Prompt Format:** 
+
 ```
 <|im_start|>system
 {{system}}<|im_end|>
@@ -110,7 +160,7 @@ Dolphin-2.9.4 has a variety of instruction following, conversational, and coding
 {{prompt}}<|im_end|>
 <|im_start|>assistant
 
-``` 
+```
 
 **Template Name:** chatml  
 
@@ -124,6 +174,7 @@ Dolphin-2.9.4 has a variety of instruction following, conversational, and coding
 ---
 
 # Financial GPT
+
 FinGPT is deeply committed to fostering an open-source ecosystem dedicated to Financial Large Language Models (FinLLMs). FinGPT envisions democratizing access to both financial data and FinLLMs. It stands as an emblem of untapped potential within open finance, aspiring to be a significant catalyst stimulating innovation and refinement within the financial domain. Note: Nothing herein is financial advice, and NOT a recommendation to trade real money  
 
 **Model Intention:** It's a professional stock market analyst. It can provide an analysis and prediction for the companies' stock price movement for the upcoming weeks.  
@@ -143,12 +194,13 @@ FinGPT is deeply committed to fostering an open-source ecosystem dedicated to Fi
 **Context Length:** 4096 tokens  
 
 **Prompt Format:** 
+
 ```
 [INST]<<SYS>>
 {{systemp}}<</SYS>>
 
 Let's first analyze the positive developments and potential concerns for {{prompt}}. Come up with 2-4 most important factors respectively and keep them concise. Most factors should be inferred from company related news. Then make your prediction of the {{prompt}} stock price movement for next week. Provide a summary analysis to support your prediction.[/INST]
-``` 
+```
 
 **Template Name:** llama  
 
@@ -162,6 +214,7 @@ Let's first analyze the positive developments and potential concerns for {{promp
 ---
 
 # Llama3.2 3B
+
 The Meta Llama 3.1 is pretrained and instruction tuned generative models in 8B sizes (text in/text out). It is optimized for multilingual dialogue use cases (English, German, French, Italian, Portuguese, Hindi, Spanish, and Thai) and outperform closed chat models on common benchmarks.  
 
 **Model Intention:** The latest Llama 3.2 is optimized for multilingual dialogue use cases, including agentic retrieval and summarization tasks  
@@ -183,6 +236,7 @@ The Meta Llama 3.1 is pretrained and instruction tuned generative models in 8B s
 **Context Length:** 8192 tokens  
 
 **Prompt Format:** 
+
 ```
 <|begin_of_text|><|start_header_id|>user<|end_header_id|>
 
@@ -190,7 +244,7 @@ The Meta Llama 3.1 is pretrained and instruction tuned generative models in 8B s
 
 assistant
 
-``` 
+```
 
 **Template Name:** llama3.2  
 
@@ -204,6 +258,7 @@ assistant
 ---
 
 # Mistral 7B v0.3
+
 The Mistral 7B v0.3 Large is a pretrained generative text model with 7 billion parameters. It extended vocabulary to 32768 and supports function calling.  
 
 **Model Intention:** It's a 7B large model for Q&A purpose. But it requires a high-end device to run.  
@@ -223,9 +278,10 @@ The Mistral 7B v0.3 Large is a pretrained generative text model with 7 billion p
 **Context Length:** 8192 tokens  
 
 **Prompt Format:** 
+
 ```
 <s>[INST]{{prompt}}[/INST]</s>
-``` 
+```
 
 **Template Name:** Mistral  
 
@@ -239,6 +295,7 @@ The Mistral 7B v0.3 Large is a pretrained generative text model with 7 billion p
 ---
 
 # OpenChat 3.6(0522)
+
 OpenChat is an innovative library of open-source language models, fine-tuned with C-RLFT - a strategy inspired by offline reinforcement learning. Our models learn from mixed-quality data without preference labels, delivering exceptional performance on par with ChatGPT, even with a 7B model. Despite our simple approach, we are committed to developing a high-performance, commercially viable, open-source large language model, and we continue to make significant strides toward this vision.  
 
 **Model Intention:** the Llama-3 based version OpenChat 3.6 20240522, outperforming official Llama 3 8B Instruct.  
@@ -258,10 +315,11 @@ OpenChat is an innovative library of open-source language models, fine-tuned wit
 **Context Length:** 8192 tokens  
 
 **Prompt Format:** 
+
 ```
 {{system}}
 GPT4 Correct User: {{prompt}}<|end_of_turn|>GPT4 Correct Assistant: 
-``` 
+```
 
 **Template Name:** Mistral  
 
@@ -275,6 +333,7 @@ GPT4 Correct User: {{prompt}}<|end_of_turn|>GPT4 Correct Assistant:
 ---
 
 # Phi-3 Vision
+
 The Phi-3 4K-Instruct is a 3.8B parameters, lightweight, state-of-the-art open model. It is optimized for the instruction following and safety measures. It is good at common sense, language understanding, math, code, long context and logical reasoning, Phi-3 Mini-4K-Instruct showcased a robust and state-of-the-art performance among models with less than 13 billion parameters.  
 
 **Model Intention:** It's a Microsoft Phi-3B model with visual support. It can understand images as well as text  
@@ -294,11 +353,12 @@ The Phi-3 4K-Instruct is a 3.8B parameters, lightweight, state-of-the-art open m
 **Context Length:** 4096 tokens  
 
 **Prompt Format:** 
+
 ```
 <|user|>
 {{prompt}} <|end|>
 <|assistant|>
-``` 
+```
 
 **Template Name:** PHI3  
 
@@ -312,6 +372,7 @@ The Phi-3 4K-Instruct is a 3.8B parameters, lightweight, state-of-the-art open m
 ---
 
 # Yi 1.5 6B Chat
+
 Yi-1.5 is an upgraded version which delivers stronger performance in coding, math, reasoning, and instruction-following capability, while still maintaining excellent capabilities in language understanding, commonsense reasoning, and reading comprehension. It is continuously pre-trained on Yi with a high-quality corpus of 500B tokens and fine-tuned on 3M diverse fine-tuning samples. The Yi series models are the next generation of open-source large language models trained from scratch by 01.AI. The Yi series models become one of the strongest LLM worldwide, showing promise in language understanding, commonsense reasoning, reading comprehension, and more.  
 
 **Model Intention:** It's a 6B model and can understand English and Chinese. It's good for coding, math, reasoning and language understanding  
@@ -335,13 +396,14 @@ Yi-1.5 is an upgraded version which delivers stronger performance in coding, mat
 **Context Length:** 4096 tokens  
 
 **Prompt Format:** 
+
 ```
 <|im_start|>user
 <|im_end|>
 {{prompt}}
 <|im_start|>assistant
 
-``` 
+```
 
 **Template Name:** yi  
 
@@ -355,6 +417,7 @@ Yi-1.5 is an upgraded version which delivers stronger performance in coding, mat
 ---
 
 # Google Gemma 2B
+
 Gemma is a family of lightweight, state-of-the-art open models built from the same research and technology used to create the Gemini models. Developed by Google DeepMind and other teams across Google, Gemma is named after the Latin gemma, meaning 'precious stone.' The Gemma model weights are supported by developer tools that promote innovation, collaboration, and the responsible use of artificial intelligence (AI).  
 
 **Model Intention:** It's a 2B large model for Q&A purpose. But it requires a high-end device to run.  
@@ -374,12 +437,13 @@ Gemma is a family of lightweight, state-of-the-art open models built from the sa
 **Context Length:** 8192 tokens  
 
 **Prompt Format:** 
+
 ```
 <bos><start_of_turn>user
 {{prompt}}<end_of_turn>
 <start_of_turn>model
 
-``` 
+```
 
 **Template Name:** gemma  
 
@@ -393,6 +457,7 @@ Gemma is a family of lightweight, state-of-the-art open models built from the sa
 ---
 
 # StarCoder2 3B
+
 StarCoder2-3B model is a 3B parameter model trained on 17 programming languages from The Stack v2, with opt-out requests excluded. The model uses Grouped Query Attention, a context window of 16,384 tokens with a sliding window attention of 4,096 tokens, and was trained using the Fill-in-the-Middle objective on 3+ trillion tokens  
 
 **Model Intention:** The model is good at 17 programming languages. By just start with your codes, the model will finish it.  
@@ -412,10 +477,11 @@ StarCoder2-3B model is a 3B parameter model trained on 17 programming languages
 **Context Length:** 16384 tokens  
 
 **Prompt Format:** 
+
 ```
 {{prompt}}
 
-``` 
+```
 
 **Template Name:** starcoder  
 
@@ -429,6 +495,7 @@ StarCoder2-3B model is a 3B parameter model trained on 17 programming languages
 ---
 
 # Qwen2.5 7B Chat
+
 Qwen is the large language model and large multimodal model series of the Qwen Team, Alibaba Group. It supports both Chinese and English. 通义千问是阿里巴巴公司开发的大大预言模型，支持中英文双语。  
 
 **Model Intention:** Qwen2.5 is the latest series models that is good at multilingual, coding, mathematics, reasoning, etc  
@@ -448,6 +515,7 @@ Qwen is the large language model and large multimodal model series of the Qwen T
 **Context Length:** 4096 tokens  
 
 **Prompt Format:** 
+
 ```
 <|im_start|>system
 {{system}}<|im_end|>
@@ -455,7 +523,7 @@ Qwen is the large language model and large multimodal model series of the Qwen T
 {{prompt}}<|im_end|>
 <|im_start|>assistant
 
-``` 
+```
 
 **Template Name:** chatml  
 
@@ -469,6 +537,7 @@ Qwen is the large language model and large multimodal model series of the Qwen T
 ---
 
 # Qwen2 1.5B Chat
+
 Qwen is the large language model and large multimodal model series of the Qwen Team, Alibaba Group. It supports both Chinese and English. 通义千问是阿里巴巴公司开发的大大预言模型，支持中英文双语。  
 
 **Model Intention:** Qwen2.5 is the latest series models that is good at multilingual, coding, mathematics, reasoning, etc  
@@ -488,6 +557,7 @@ Qwen is the large language model and large multimodal model series of the Qwen T
 **Context Length:** 2048 tokens  
 
 **Prompt Format:** 
+
 ```
 <|im_start|>system
 {{system}}<|im_end|>
@@ -495,7 +565,7 @@ Qwen is the large language model and large multimodal model series of the Qwen T
 {{prompt}}<|im_end|>
 <|im_start|>assistant
 
-``` 
+```
 
 **Template Name:** chatml  
 
@@ -509,6 +579,7 @@ Qwen is the large language model and large multimodal model series of the Qwen T
 ---
 
 # Qwen2 3B Chat
+
 Qwen is the large language model and large multimodal model series of the Qwen Team, Alibaba Group. It supports both Chinese and English. 通义千问是阿里巴巴公司开发的大大预言模型，支持中英文双语。  
 
 **Model Intention:** Qwen2.5 is the latest series models that is good at multilingual, coding, mathematics, reasoning, etc  
@@ -528,6 +599,7 @@ Qwen is the large language model and large multimodal model series of the Qwen T
 **Context Length:** 2048 tokens  
 
 **Prompt Format:** 
+
 ```
 <|im_start|>system
 {{system}}<|im_end|>
@@ -535,7 +607,7 @@ Qwen is the large language model and large multimodal model series of the Qwen T
 {{prompt}}<|im_end|>
 <|im_start|>assistant
 
-``` 
+```
 
 **Template Name:** chatml  
 
@@ -549,6 +621,7 @@ Qwen is the large language model and large multimodal model series of the Qwen T
 ---
 
 # Dophin 2.9.2 Qwen2 7B
+
 This model is based on Mistral-7b-v0.2 with 16k context lengths. It's a uncensored model and supports a variety of instruction, conversational, and coding skills.  
 
 **Model Intention:** It's a uncensored and good skilled English modal best for high performance iPhone, iPad & Mac  
@@ -568,6 +641,7 @@ This model is based on Mistral-7b-v0.2 with 16k context lengths. It's a uncensor
 **Context Length:** 2048 tokens  
 
 **Prompt Format:** 
+
 ```
 <|im_start|>system
 {{system}}<|im_end|>
@@ -575,7 +649,7 @@ This model is based on Mistral-7b-v0.2 with 16k context lengths. It's a uncensor
 {{prompt}}<|im_end|>
 <|im_start|>assistant
 
-``` 
+```
 
 **Template Name:** chatml  
 
@@ -583,7 +657,4 @@ This model is based on Mistral-7b-v0.2 with 16k context lengths. It's a uncensor
 
 **Add EOS Token:** No  
 
-**Parse Special Tokens:** Yes  
-
-
----
+**Parse Special Tokens:** Yes