gguf endpoints_compatible region:us conversational
---
{}
---
# 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/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)  

**Model License:** [License Info](https://raw.githubusercontent.com/google-deepmind/gemma/main/LICENSE)  

**Model Description:** 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.  

**Developer:** [https://huggingface.co/jinaai](https://huggingface.co/jinaai)  

**Update Date:** 2024-10-02  

**File Size:** 986 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  


---

# 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.  

**Model URL:** [https://huggingface.co/flyingfishinwater/good_and_small_models/resolve/main/llama-3.1-whiterabbitneo-2-8b-q4_k_m.gguf?download=true](https://huggingface.co/flyingfishinwater/good_and_small_models/resolve/main/llama-3.1-whiterabbitneo-2-8b-q4_k_m.gguf?download=true)  

**Model Info URL:** [https://huggingface.co/WhiteRabbitNeo/Llama-3.1-WhiteRabbitNeo-2-8B](https://huggingface.co/WhiteRabbitNeo/Llama-3.1-WhiteRabbitNeo-2-8B)  

**Model License:** [License Info](https://raw.githubusercontent.com/google-deepmind/gemma/main/LICENSE)  

**Model Description:** 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.  

**Developer:** [https://huggingface.co/WhiteRabbitNeo](https://huggingface.co/WhiteRabbitNeo)  

**Update Date:** 2024-10-02  

**File Size:** 4920 MB  

**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  

**Add BOS Token:** Yes  

**Add EOS Token:** No  

**Parse Special Tokens:** Yes  


---

# 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.  

**Model URL:** [https://huggingface.co/flyingfishinwater/good_and_small_models/resolve/main/dolphin-2.9.4-gemma2-2b-Q4_K_M.gguf?download=true](https://huggingface.co/flyingfishinwater/good_and_small_models/resolve/main/dolphin-2.9.4-gemma2-2b-Q4_K_M.gguf?download=true)  

**Model Info URL:** [https://huggingface.co/cognitivecomputations/dolphin-2.9.4-gemma2-2b](https://huggingface.co/cognitivecomputations/dolphin-2.9.4-gemma2-2b)  

**Model License:** [License Info](https://raw.githubusercontent.com/google-deepmind/gemma/main/LICENSE)  

**Model Description:** 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.  

**Developer:** [https://huggingface.co/cognitivecomputations](https://huggingface.co/cognitivecomputations)  

**Update Date:** 2024-08-20  

**File Size:** 1710 MB  

**Context Length:** 4096 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  


---

# 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.  

**Model URL:** [https://huggingface.co/flyingfishinwater/good_and_small_models/resolve/main/FinGPT-7B-Q3_K_M.gguf?download=true](https://huggingface.co/flyingfishinwater/good_and_small_models/resolve/main/FinGPT-7B-Q3_K_M.gguf?download=true)  

**Model Info URL:** [https://huggingface.co/FinGPT/fingpt-forecaster_dow30_llama2-7b_lora](https://huggingface.co/FinGPT/fingpt-forecaster_dow30_llama2-7b_lora)  

**Model License:** [License Info](https://llama.meta.com/llama3/license/)  

**Model Description:** 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  

**Developer:** [https://ai4finance.org/](https://ai4finance.org/)  

**File Size:** 3310 MB  

**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  

**Add BOS Token:** Yes  

**Add EOS Token:** No  

**Parse Special Tokens:** Yes  


---

# 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  

**Model URL:** [https://huggingface.co/flyingfishinwater/good_and_small_models/resolve/main/Llama-3.2-3B-Instruct-Q4_K_M.gguf?download=true](https://huggingface.co/flyingfishinwater/good_and_small_models/resolve/main/Llama-3.2-3B-Instruct-Q4_K_M.gguf?download=true)  

**Model Info URL:** [https://huggingface.co/meta-llama/Llama-3.2-3B-Instruct](https://huggingface.co/meta-llama/Llama-3.2-3B-Instruct)  

**Model License:** [License Info](https://llama.meta.com/llama3/license/)  

**Model Description:** 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.  

**Developer:** [https://llama.meta.com/](https://llama.meta.com/)  

**Update Date:** 2024-07-24  

**File Size:** 2020 MB  

**Context Length:** 8192 tokens  

**Prompt Format:** 

```
<|begin_of_text|><|start_header_id|>user<|end_header_id|>

{{prompt}}<|eot_id|><|start_header_id|>assistant<|end_header_id|>

assistant

```

**Template Name:** llama3.2  

**Add BOS Token:** Yes  

**Add EOS Token:** No  

**Parse Special Tokens:** Yes  


---

# 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.  

**Model URL:** [https://huggingface.co/flyingfishinwater/good_and_small_models/resolve/main/Mistral-7B-Instruct-v0.3.Q3_K_M.gguf?download=true](https://huggingface.co/flyingfishinwater/good_and_small_models/resolve/main/Mistral-7B-Instruct-v0.3.Q3_K_M.gguf?download=true)  

**Model Info URL:** [https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.3](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.3)  

**Model License:** [License Info](https://www.apache.org/licenses/LICENSE-2.0)  

**Model Description:** 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.  

**Developer:** [https://mistral.ai/](https://mistral.ai/)  

**File Size:** 3520 MB  

**Context Length:** 8192 tokens  

**Prompt Format:** 

```
<s>[INST]{{prompt}}[/INST]</s>
```

**Template Name:** Mistral  

**Add BOS Token:** Yes  

**Add EOS Token:** No  

**Parse Special Tokens:** Yes  


---

# 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.  

**Model URL:** [https://huggingface.co/flyingfishinwater/good_and_small_models/resolve/main/openchat-3.6-8b-20240522-Q3_K_M.gguf?download=true](https://huggingface.co/flyingfishinwater/good_and_small_models/resolve/main/openchat-3.6-8b-20240522-Q3_K_M.gguf?download=true)  

**Model Info URL:** [https://huggingface.co/openchat/openchat-3.6-8b-20240522](https://huggingface.co/openchat/openchat-3.6-8b-20240522)  

**Model License:** [License Info](https://www.apache.org/licenses/LICENSE-2.0)  

**Model Description:** 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.  

**Developer:** [https://openchat.team/](https://openchat.team/)  

**File Size:** 4020 MB  

**Context Length:** 8192 tokens  

**Prompt Format:** 

```
{{system}}
GPT4 Correct User: {{prompt}}<|end_of_turn|>GPT4 Correct Assistant: 
```

**Template Name:** Mistral  

**Add BOS Token:** Yes  

**Add EOS Token:** No  

**Parse Special Tokens:** Yes  


---

# 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  

**Model URL:** [https://huggingface.co/flyingfishinwater/good_and_small_models/resolve/main/Phi-3-mini-4k-instruct-q4.gguf?download=true](https://huggingface.co/flyingfishinwater/good_and_small_models/resolve/main/Phi-3-mini-4k-instruct-q4.gguf?download=true)  

**Model Info URL:** [https://huggingface.co/microsoft/Phi-3-mini-4k-instruct](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct)  

**Model License:** [License Info](https://opensource.org/license/mit)  

**Model Description:** 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.  

**Developer:** [https://huggingface.co/microsoft/Phi-3-mini-4k-instruct](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct)  

**File Size:** 2320 MB  

**Context Length:** 4096 tokens  

**Prompt Format:** 

```
<|user|>
{{prompt}} <|end|>
<|assistant|>
```

**Template Name:** PHI3  

**Add BOS Token:** Yes  

**Add EOS Token:** No  

**Parse Special Tokens:** Yes  


---

# 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  

**Model URL:** [https://huggingface.co/flyingfishinwater/good_and_small_models/resolve/main/Yi-1.5-6B-Q3_K_M.gguf?download=true](https://huggingface.co/flyingfishinwater/good_and_small_models/resolve/main/Yi-1.5-6B-Q3_K_M.gguf?download=true)  

**Model Info URL:** [https://huggingface.co/01-ai/Yi-1.5-6B-Chat](https://huggingface.co/01-ai/Yi-1.5-6B-Chat)  

**Model License:** [License Info](https://www.apache.org/licenses/LICENSE-2.0)  

**Model Description:** 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.  

**Developer:** [https://01.ai/](https://01.ai/)  

**Update Date:** 2024-05-12  

**Update History:** Yi-1.5 is an upgraded version of Yi. It is continuously pre-trained on Yi with a high-quality corpus of 500B tokens and fine-tuned on 3M diverse fine-tuning samples. Yi-1.5 delivers stronger performance in coding, math, reasoning, and instruction-following capability, while still maintaining excellent capabilities in language understanding, commonsense reasoning, and reading comprehension  

**File Size:** 2990 MB  

**Context Length:** 4096 tokens  

**Prompt Format:** 

```
<|im_start|>user
<|im_end|>
{{prompt}}
<|im_start|>assistant

```

**Template Name:** yi  

**Add BOS Token:** Yes  

**Add EOS Token:** No  

**Parse Special Tokens:** Yes  


---

# 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.  

**Model URL:** [https://huggingface.co/flyingfishinwater/good_and_small_models/resolve/main/gemma-2b-it-q8_0.gguf?download=true](https://huggingface.co/flyingfishinwater/good_and_small_models/resolve/main/gemma-2b-it-q8_0.gguf?download=true)  

**Model Info URL:** [https://huggingface.co/google/gemma-2b](https://huggingface.co/google/gemma-2b)  

**Model License:** [License Info](https://www.apache.org/licenses/LICENSE-2.0)  

**Model Description:** 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).  

**Developer:** [https://huggingface.co/google](https://huggingface.co/google)  

**File Size:** 2669 MB  

**Context Length:** 8192 tokens  

**Prompt Format:** 

```
<bos><start_of_turn>user
{{prompt}}<end_of_turn>
<start_of_turn>model

```

**Template Name:** gemma  

**Add BOS Token:** Yes  

**Add EOS Token:** No  

**Parse Special Tokens:** Yes  


---

# 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.  

**Model URL:** [https://huggingface.co/flyingfishinwater/good_and_small_models/resolve/main/starcoder2-3b-instruct-gguf_Q8_0.gguf?download=true](https://huggingface.co/flyingfishinwater/good_and_small_models/resolve/main/starcoder2-3b-instruct-gguf_Q8_0.gguf?download=true)  

**Model Info URL:** [https://huggingface.co/bigcode/starcoder2-3b](https://huggingface.co/bigcode/starcoder2-3b)  

**Model License:** [License Info](https://www.apache.org/licenses/LICENSE-2.0)  

**Model Description:** 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  

**Developer:** [https://www.bigcode-project.org/](https://www.bigcode-project.org/)  

**File Size:** 3220 MB  

**Context Length:** 16384 tokens  

**Prompt Format:** 

```
{{prompt}}

```

**Template Name:** starcoder  

**Add BOS Token:** Yes  

**Add EOS Token:** No  

**Parse Special Tokens:** Yes  


---

# 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  

**Model URL:** [https://huggingface.co/flyingfishinwater/good_and_small_models/resolve/main/Qwen2-7B-Instruct-Q3_K_S.gguf?download=true](https://huggingface.co/flyingfishinwater/good_and_small_models/resolve/main/Qwen2-7B-Instruct-Q3_K_S.gguf?download=true)  

**Model Info URL:** [https://huggingface.co/Qwen/Qwen2.5-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct)  

**Model License:** [License Info](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct/raw/main/LICENSE)  

**Model Description:** 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。  

**Developer:** [https://huggingface.co/Qwen](https://huggingface.co/Qwen)  

**File Size:** 3990 MB  

**Context Length:** 4096 tokens  

**Prompt Format:** 

```
<|im_start|>system
{{system}}<|im_end|>
<|im_start|>
{{prompt}}<|im_end|>
<|im_start|>assistant

```

**Template Name:** chatml  

**Add BOS Token:** Yes  

**Add EOS Token:** No  

**Parse Special Tokens:** Yes  


---

# 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  

**Model URL:** [https://huggingface.co/flyingfishinwater/good_and_small_models/resolve/main/qwen2.5-1.5b-instruct-q4_k_m.gguf?download=true](https://huggingface.co/flyingfishinwater/good_and_small_models/resolve/main/qwen2.5-1.5b-instruct-q4_k_m.gguf?download=true)  

**Model Info URL:** [https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct-GGUF](https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct-GGUF)  

**Model License:** [License Info](https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct-GGUF/raw/main/LICENSE)  

**Model Description:** 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。  

**Developer:** [https://huggingface.co/Qwen](https://huggingface.co/Qwen)  

**File Size:** 1120 MB  

**Context Length:** 2048 tokens  

**Prompt Format:** 

```
<|im_start|>system
{{system}}<|im_end|>
<|im_start|>
{{prompt}}<|im_end|>
<|im_start|>assistant

```

**Template Name:** chatml  

**Add BOS Token:** Yes  

**Add EOS Token:** No  

**Parse Special Tokens:** Yes  


---

# 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  

**Model URL:** [https://huggingface.co/flyingfishinwater/good_and_small_models/resolve/main/qwen2.5-3b-instruct-q4_k_m.gguf?download=true](https://huggingface.co/flyingfishinwater/good_and_small_models/resolve/main/qwen2.5-3b-instruct-q4_k_m.gguf?download=true)  

**Model Info URL:** [https://huggingface.co/Qwen/Qwen2.5-3B](https://huggingface.co/Qwen/Qwen2.5-3B)  

**Model License:** [License Info](https://huggingface.co/Qwen/Qwen2.5-3B/raw/main/LICENSE)  

**Model Description:** 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。  

**Developer:** [https://huggingface.co/Qwen](https://huggingface.co/Qwen)  

**File Size:** 1930 MB  

**Context Length:** 2048 tokens  

**Prompt Format:** 

```
<|im_start|>system
{{system}}<|im_end|>
<|im_start|>
{{prompt}}<|im_end|>
<|im_start|>assistant

```

**Template Name:** chatml  

**Add BOS Token:** Yes  

**Add EOS Token:** No  

**Parse Special Tokens:** Yes  


---

# 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  

**Model URL:** [https://huggingface.co/flyingfishinwater/good_and_small_models/resolve/main/dolphin-2.9.2-qwen2-7b-Q3_K_S.gguf?download=true](https://huggingface.co/flyingfishinwater/good_and_small_models/resolve/main/dolphin-2.9.2-qwen2-7b-Q3_K_S.gguf?download=true)  

**Model Info URL:** [https://huggingface.co/cognitivecomputations/dolphin-2.9.2-qwen2-7b-gguf](https://huggingface.co/cognitivecomputations/dolphin-2.9.2-qwen2-7b-gguf)  

**Model License:** [License Info](https://www.apache.org/licenses/LICENSE-2.0)  

**Model Description:** 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.  

**Developer:** [https://erichartford.com/](https://erichartford.com/)  

**File Size:** 3490 MB  

**Context Length:** 2048 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  