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  license: apache-2.0
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  ---
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  # Llama3 8B
 
5
  Llama 3 is the latest and most advanced LLM trained over 15T tokens, which improves its comprehension and handling of complex language nuances. It features an extended context window of 8k tokens allowing the model to access more information from lengthy passages for more informed decision-making.
6
 
7
  **Model Intention:** The latest Llama 3 enabling more accurate and informative responses to complex queries in both English and multilingual contexts.
8
 
9
- **Model URL:** [https://huggingface.co/flyingfishinwater/goodmodels/resolve/main/Meta-Llama-3-8B-Instruct-Q4_K_M.gguf?download=true](https://huggingface.co/flyingfishinwater/goodmodels/resolve/main/Meta-Llama-3-8B-Instruct-Q4_K_M.gguf?download=true)
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  **Model Info URL:** [https://huggingface.co/meta-llama/Meta-Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B)
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@@ -21,6 +22,7 @@ Llama 3 is the latest and most advanced LLM trained over 15T tokens, which impro
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  **Context Length:** 8192 tokens
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  **Prompt Format:**
 
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  ```
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  <|start_header_id|>user<|end_header_id|>
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@@ -28,7 +30,7 @@ Llama 3 is the latest and most advanced LLM trained over 15T tokens, which impro
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  assistant
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- ```
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33
  **Template Name:** llama
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@@ -42,11 +44,12 @@ assistant
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  ---
43
 
44
  # LiteLlama
 
45
  It's a very small LLAMA2 model with only 460M parameters trained with 1T tokens. It's best for testing.
46
 
47
  **Model Intention:** This is a 460 parameters' very small model for test purpose only
48
 
49
- **Model URL:** [https://huggingface.co/flyingfishinwater/goodmodels/resolve/main/LiteLlama-460M-1T-Q8_0.gguf?download=true](https://huggingface.co/flyingfishinwater/goodmodels/resolve/main/LiteLlama-460M-1T-Q8_0.gguf?download=true)
50
 
51
  **Model Info URL:** [https://huggingface.co/ahxt/LiteLlama-460M-1T](https://huggingface.co/ahxt/LiteLlama-460M-1T)
52
 
@@ -61,10 +64,11 @@ It's a very small LLAMA2 model with only 460M parameters trained with 1T tokens.
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  **Context Length:** 1024 tokens
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63
  **Prompt Format:**
 
64
  ```
65
  <human>: {{prompt}}
66
  <bot>:
67
- ```
68
 
69
  **Template Name:** TinyLlama
70
 
@@ -78,11 +82,12 @@ It's a very small LLAMA2 model with only 460M parameters trained with 1T tokens.
78
  ---
79
 
80
  # TinyLlama-1.1B-chat
 
81
  The TinyLlama project aims to pretrain a 1.1B Llama model on 3 trillion tokens. With some proper optimization, we can achieve this within a span of just 90 days using 16 A100-40G GPUs. The training has started on 2023-09-01.
82
 
83
  **Model Intention:** It's good for question & answer.
84
 
85
- **Model URL:** [https://huggingface.co/flyingfishinwater/goodmodels/resolve/main/tinyllama-1.1B-chat-v1.0-Q8_0.gguf?download=true](https://huggingface.co/flyingfishinwater/goodmodels/resolve/main/tinyllama-1.1B-chat-v1.0-Q8_0.gguf?download=true)
86
 
87
  **Model Info URL:** [https://huggingface.co/TinyLlama/TinyLlama-1.1B-Chat-v1.0](https://huggingface.co/TinyLlama/TinyLlama-1.1B-Chat-v1.0)
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@@ -97,9 +102,10 @@ The TinyLlama project aims to pretrain a 1.1B Llama model on 3 trillion tokens.
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  **Context Length:** 4096 tokens
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99
  **Prompt Format:**
 
100
  ```
101
  <|user|>{{prompt}}</s><|assistant|>
102
- ```
103
 
104
  **Template Name:** TinyLlama
105
 
@@ -113,11 +119,12 @@ The TinyLlama project aims to pretrain a 1.1B Llama model on 3 trillion tokens.
113
  ---
114
 
115
  # Mistral 7B v0.2
 
116
  The Mistral-7B-v0.2 Large Language Model (LLM) is a pretrained generative text model with 7 billion parameters. Mistral-7B-v0.2 outperforms Llama 2 13B on all benchmarks we tested.
117
 
118
  **Model Intention:** It's a 7B large model for Q&A purpose. But it requires a high-end device to run.
119
 
120
- **Model URL:** [https://huggingface.co/flyingfishinwater/goodmodels/resolve/main/mistral-7b-instruct-v0.2.Q8_0.gguf?download=true](https://huggingface.co/flyingfishinwater/goodmodels/resolve/main/mistral-7b-instruct-v0.2.Q8_0.gguf?download=true)
121
 
122
  **Model Info URL:** [https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2)
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@@ -132,9 +139,10 @@ The Mistral-7B-v0.2 Large Language Model (LLM) is a pretrained generative text m
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  **Context Length:** 4096 tokens
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134
  **Prompt Format:**
 
135
  ```
136
  <s>[INST]{{prompt}}[/INST]</s>
137
- ```
138
 
139
  **Template Name:** Mistral
140
 
@@ -148,11 +156,12 @@ The Mistral-7B-v0.2 Large Language Model (LLM) is a pretrained generative text m
148
  ---
149
 
150
  # OpenChat 3.5(0106)
 
151
  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.
152
 
153
  **Model Intention:** It's a 7B large model and performs really good for Q&A. But it requires a high-end device to run.
154
 
155
- **Model URL:** [https://huggingface.co/flyingfishinwater/goodmodels/resolve/main/openchat-3.5-0106.Q3_K_M.gguf?download=true](https://huggingface.co/flyingfishinwater/goodmodels/resolve/main/openchat-3.5-0106.Q3_K_M.gguf?download=true)
156
 
157
  **Model Info URL:** [https://huggingface.co/openchat/openchat_3.5](https://huggingface.co/openchat/openchat_3.5)
158
 
@@ -167,9 +176,10 @@ OpenChat is an innovative library of open-source language models, fine-tuned wit
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  **Context Length:** 8192 tokens
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169
  **Prompt Format:**
 
170
  ```
171
  GPT4 Correct User: {{prompt}}<|end_of_turn|>GPT4 Correct Assistant:
172
- ```
173
 
174
  **Template Name:** Mistral
175
 
@@ -182,32 +192,35 @@ GPT4 Correct User: {{prompt}}<|end_of_turn|>GPT4 Correct Assistant:
182
 
183
  ---
184
 
185
- # Phi-2
186
- Phi-2 is a Transformer with 2.7 billion parameters. It was trained using the same data sources as Phi-1.5, augmented with a new data source that consists of various NLP synthetic texts and filtered websites (for safety and educational value). When assessed against benchmarks testing common sense, language understanding, and logical reasoning, Phi-2 showcased a nearly state-of-the-art performance among models with less than 13 billion parameters.
 
187
 
188
- **Model Intention:** It's a 2.7B model and is intended for QA, chat, and code purposes
189
 
190
- **Model URL:** [https://huggingface.co/ggml-org/models/resolve/main/phi-2.Q5_K_M.gguf?download=true](https://huggingface.co/ggml-org/models/resolve/main/phi-2.Q5_K_M.gguf?download=true)
191
 
192
- **Model Info URL:** [https://huggingface.co/microsoft/phi-2](https://huggingface.co/microsoft/phi-2)
193
 
194
  **Model License:** [License Info](https://opensource.org/license/mit)
195
 
196
- **Model Description:** Phi-2 is a Transformer with 2.7 billion parameters. It was trained using the same data sources as Phi-1.5, augmented with a new data source that consists of various NLP synthetic texts and filtered websites (for safety and educational value). When assessed against benchmarks testing common sense, language understanding, and logical reasoning, Phi-2 showcased a nearly state-of-the-art performance among models with less than 13 billion parameters.
197
 
198
- **Developer:** [https://huggingface.co/microsoft/phi-2](https://huggingface.co/microsoft/phi-2)
199
 
200
- **File Size:** 2070 MB
201
 
202
- **Context Length:** 2048 tokens
203
 
204
  **Prompt Format:**
 
 
 
 
 
205
  ```
206
- Instruct: {{prompt}}
207
- Output:
208
- ```
209
 
210
- **Template Name:** PHI
211
 
212
  **Add BOS Token:** Yes
213
 
@@ -219,11 +232,12 @@ Output:
219
  ---
220
 
221
  # Yi 6B Chat
 
222
  The Yi series models are the next generation of open-source large language models trained from scratch by 01.AI. Targeted as a bilingual language model and trained on 3T multilingual corpus, the Yi series models become one of the strongest LLM worldwide, showing promise in language understanding, commonsense reasoning, reading comprehension, and more. For example, For English language capability, the Yi series models ranked 2nd (just behind GPT-4), outperforming other LLMs (such as LLaMA2-chat-70B, Claude 2, and ChatGPT) on the AlpacaEval Leaderboard in Dec 2023. For Chinese language capability, the Yi series models landed in 2nd place (following GPT-4), surpassing other LLMs (such as Baidu ERNIE, Qwen, and Baichuan) on the SuperCLUE in Oct 2023.
223
 
224
  **Model Intention:** It's a 6B model and can understand English and Chinese. It's good for QA and Chat
225
 
226
- **Model URL:** [https://huggingface.co/flyingfishinwater/goodmodels/resolve/main/yi-chat-6b.Q4_K_M.gguf?download=true](https://huggingface.co/flyingfishinwater/goodmodels/resolve/main/yi-chat-6b.Q4_K_M.gguf?download=true)
227
 
228
  **Model Info URL:** [https://huggingface.co/01-ai/Yi-6B-Chat](https://huggingface.co/01-ai/Yi-6B-Chat)
229
 
@@ -238,13 +252,14 @@ The Yi series models are the next generation of open-source large language model
238
  **Context Length:** 4096 tokens
239
 
240
  **Prompt Format:**
 
241
  ```
242
  <|im_start|>user
243
  <|im_end|>
244
  {{prompt}}
245
  <|im_start|>assistant
246
 
247
- ```
248
 
249
  **Template Name:** yi
250
 
@@ -258,11 +273,12 @@ The Yi series models are the next generation of open-source large language model
258
  ---
259
 
260
  # Google Gemma 2B
 
261
  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).
262
 
263
  **Model Intention:** It's a 2B large model for Q&A purpose. But it requires a high-end device to run.
264
 
265
- **Model URL:** [https://huggingface.co/flyingfishinwater/goodmodels/resolve/main/gemma-2b-it-q8_0.gguf?download=true](https://huggingface.co/flyingfishinwater/goodmodels/resolve/main/gemma-2b-it-q8_0.gguf?download=true)
266
 
267
  **Model Info URL:** [https://huggingface.co/google/gemma-2b](https://huggingface.co/google/gemma-2b)
268
 
@@ -277,12 +293,13 @@ Gemma is a family of lightweight, state-of-the-art open models built from the sa
277
  **Context Length:** 8192 tokens
278
 
279
  **Prompt Format:**
 
280
  ```
281
  <bos><start_of_turn>user
282
  {{prompt}}<end_of_turn>
283
  <start_of_turn>model
284
 
285
- ```
286
 
287
  **Template Name:** gemma
288
 
@@ -296,11 +313,12 @@ Gemma is a family of lightweight, state-of-the-art open models built from the sa
296
  ---
297
 
298
  # StarCoder2 3B
 
299
  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
300
 
301
  **Model Intention:** The model is good at 17 programming languages. By just start with your codes, the model will finish it.
302
 
303
- **Model URL:** [https://huggingface.co/flyingfishinwater/goodmodels/resolve/main/starcoder2-3b-instruct-gguf_Q8_0.gguf?download=true](https://huggingface.co/flyingfishinwater/goodmodels/resolve/main/starcoder2-3b-instruct-gguf_Q8_0.gguf?download=true)
304
 
305
  **Model Info URL:** [https://huggingface.co/bigcode/starcoder2-3b](https://huggingface.co/bigcode/starcoder2-3b)
306
 
@@ -315,10 +333,11 @@ StarCoder2-3B model is a 3B parameter model trained on 17 programming languages
315
  **Context Length:** 16384 tokens
316
 
317
  **Prompt Format:**
 
318
  ```
319
  {{prompt}}
320
 
321
- ```
322
 
323
  **Template Name:** starcoder
324
 
@@ -332,11 +351,12 @@ StarCoder2-3B model is a 3B parameter model trained on 17 programming languages
332
  ---
333
 
334
  # Chinese Tiny LLM 2B
 
335
  Chinese Tiny LLM 2B 是首个以中文为中心的大型语言模型,主要在中文语料库上进行预训练和微调,提供了对潜在偏见、中文语言能力和多语言适应性的重要洞见。
336
 
337
  **Model Intention:** 这是一个参数规模2B的中文模型,具有很好的中文理解和应答能力
338
 
339
- **Model URL:** [https://huggingface.co/flyingfishinwater/goodmodels/resolve/main/chinese-tiny-llm-2b-Q8_0.gguf?download=true](https://huggingface.co/flyingfishinwater/goodmodels/resolve/main/chinese-tiny-llm-2b-Q8_0.gguf?download=true)
340
 
341
  **Model Info URL:** [https://chinese-tiny-llm.github.io/](https://chinese-tiny-llm.github.io/)
342
 
@@ -351,13 +371,14 @@ Chinese Tiny LLM 2B 是首个以中文为中心的大型语言模型,主要在
351
  **Context Length:** 4096 tokens
352
 
353
  **Prompt Format:**
 
354
  ```
355
  <|im_start|>user
356
  {{prompt}}
357
  <|im_end|>
358
  <|im_start|>assistant
359
 
360
- ```
361
 
362
  **Template Name:** chatml
363
 
@@ -371,11 +392,12 @@ Chinese Tiny LLM 2B 是首个以中文为中心的大型语言模型,主要在
371
  ---
372
 
373
  # Qwen1.5 4B Chat
 
374
  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。
375
 
376
  **Model Intention:** It's one of the best LLM that supports Chinese and English. 这是支持中英双语的最佳的大语言模型之一。
377
 
378
- **Model URL:** [https://huggingface.co/flyingfishinwater/goodmodels/resolve/main/qwen1_5-4b-chat-q4_k_m.gguf?download=true](https://huggingface.co/flyingfishinwater/goodmodels/resolve/main/qwen1_5-4b-chat-q4_k_m.gguf?download=true)
379
 
380
  **Model Info URL:** [https://huggingface.co/Qwen/Qwen1.5-4B-Chat-GGUF](https://huggingface.co/Qwen/Qwen1.5-4B-Chat-GGUF)
381
 
@@ -390,13 +412,14 @@ Qwen is the large language model and large multimodal model series of the Qwen T
390
  **Context Length:** 32768 tokens
391
 
392
  **Prompt Format:**
 
393
  ```
394
  <|im_start|>user
395
  {{prompt}}
396
  <|im_end|>
397
  <|im_start|>assistant
398
 
399
- ```
400
 
401
  **Template Name:** chatml
402
 
@@ -410,11 +433,12 @@ Qwen is the large language model and large multimodal model series of the Qwen T
410
  ---
411
 
412
  # Dophin 2.8 Mistralv02 7B
 
413
  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.
414
 
415
  **Model Intention:** It's a uncensored and good skilled English modal best for high performance iPhone, iPad & Mac
416
 
417
- **Model URL:** [https://huggingface.co/flyingfishinwater/goodmodels/resolve/main/dolphin-2.8-mistral-7b-v02-Q2_K.gguf?download=true](https://huggingface.co/flyingfishinwater/goodmodels/resolve/main/dolphin-2.8-mistral-7b-v02-Q2_K.gguf?download=true)
418
 
419
  **Model Info URL:** [https://huggingface.co/cognitivecomputations/dolphin-2.8-mistral-7b-v02](https://huggingface.co/cognitivecomputations/dolphin-2.8-mistral-7b-v02)
420
 
@@ -429,13 +453,14 @@ This model is based on Mistral-7b-v0.2 with 16k context lengths. It's a uncensor
429
  **Context Length:** 32768 tokens
430
 
431
  **Prompt Format:**
 
432
  ```
433
  <s><|im_start|>user
434
  {{prompt}}
435
  <|im_end|>
436
  <|im_start|>assistant
437
 
438
- ```
439
 
440
  **Template Name:** chatml
441
 
@@ -449,11 +474,12 @@ This model is based on Mistral-7b-v0.2 with 16k context lengths. It's a uncensor
449
  ---
450
 
451
  # WizardLM-2 7B
 
452
  The WizardLM-2 is one of the next generation state-of-the-art large language models, which have improved performance on complex chat, multilingual, reasoning and agent.
453
 
454
  **Model Intention:** It's a state-of-the-art large language model with improved performance on complex chat, multilingual, reasoning and agent.
455
 
456
- **Model URL:** [https://huggingface.co/flyingfishinwater/goodmodels/resolve/main/WizardLM-2-7B.Q3_K_M.gguf?download=true](https://huggingface.co/flyingfishinwater/goodmodels/resolve/main/WizardLM-2-7B.Q3_K_M.gguf?download=true)
457
 
458
  **Model Info URL:** [https://huggingface.co/MaziyarPanahi/WizardLM-2-7B-GGUF](https://huggingface.co/MaziyarPanahi/WizardLM-2-7B-GGUF)
459
 
@@ -468,11 +494,12 @@ The WizardLM-2 is one of the next generation state-of-the-art large language mod
468
  **Context Length:** 32768 tokens
469
 
470
  **Prompt Format:**
 
471
  ```
472
  A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions.
473
  USER: {{prompt}}
474
  ASSISTANT:
475
- ```
476
 
477
  **Template Name:** chatml
478
 
@@ -480,7 +507,4 @@ ASSISTANT:
480
 
481
  **Add EOS Token:** No
482
 
483
- **Parse Special Tokens:** Yes
484
-
485
-
486
- ---
 
2
  license: apache-2.0
3
  ---
4
  # Llama3 8B
5
+
6
  Llama 3 is the latest and most advanced LLM trained over 15T tokens, which improves its comprehension and handling of complex language nuances. It features an extended context window of 8k tokens allowing the model to access more information from lengthy passages for more informed decision-making.
7
 
8
  **Model Intention:** The latest Llama 3 enabling more accurate and informative responses to complex queries in both English and multilingual contexts.
9
 
10
+ **Model URL:** [https://huggingface.co/flyingfishinwater/good_and_small_models/resolve/main/Meta-Llama-3-8B-Instruct-Q4_K_M.gguf?download=true](https://huggingface.co/flyingfishinwater/good_and_small_models/resolve/main/Meta-Llama-3-8B-Instruct-Q4_K_M.gguf?download=true)
11
 
12
  **Model Info URL:** [https://huggingface.co/meta-llama/Meta-Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B)
13
 
 
22
  **Context Length:** 8192 tokens
23
 
24
  **Prompt Format:**
25
+
26
  ```
27
  <|start_header_id|>user<|end_header_id|>
28
 
 
30
 
31
  assistant
32
 
33
+ ```
34
 
35
  **Template Name:** llama
36
 
 
44
  ---
45
 
46
  # LiteLlama
47
+
48
  It's a very small LLAMA2 model with only 460M parameters trained with 1T tokens. It's best for testing.
49
 
50
  **Model Intention:** This is a 460 parameters' very small model for test purpose only
51
 
52
+ **Model URL:** [https://huggingface.co/flyingfishinwater/good_and_small_models/resolve/main/LiteLlama-460M-1T-Q8_0.gguf?download=true](https://huggingface.co/flyingfishinwater/good_and_small_models/resolve/main/LiteLlama-460M-1T-Q8_0.gguf?download=true)
53
 
54
  **Model Info URL:** [https://huggingface.co/ahxt/LiteLlama-460M-1T](https://huggingface.co/ahxt/LiteLlama-460M-1T)
55
 
 
64
  **Context Length:** 1024 tokens
65
 
66
  **Prompt Format:**
67
+
68
  ```
69
  <human>: {{prompt}}
70
  <bot>:
71
+ ```
72
 
73
  **Template Name:** TinyLlama
74
 
 
82
  ---
83
 
84
  # TinyLlama-1.1B-chat
85
+
86
  The TinyLlama project aims to pretrain a 1.1B Llama model on 3 trillion tokens. With some proper optimization, we can achieve this within a span of just 90 days using 16 A100-40G GPUs. The training has started on 2023-09-01.
87
 
88
  **Model Intention:** It's good for question & answer.
89
 
90
+ **Model URL:** [https://huggingface.co/flyingfishinwater/good_and_small_models/resolve/main/tinyllama-1.1B-chat-v1.0-Q8_0.gguf?download=true](https://huggingface.co/flyingfishinwater/good_and_small_models/resolve/main/tinyllama-1.1B-chat-v1.0-Q8_0.gguf?download=true)
91
 
92
  **Model Info URL:** [https://huggingface.co/TinyLlama/TinyLlama-1.1B-Chat-v1.0](https://huggingface.co/TinyLlama/TinyLlama-1.1B-Chat-v1.0)
93
 
 
102
  **Context Length:** 4096 tokens
103
 
104
  **Prompt Format:**
105
+
106
  ```
107
  <|user|>{{prompt}}</s><|assistant|>
108
+ ```
109
 
110
  **Template Name:** TinyLlama
111
 
 
119
  ---
120
 
121
  # Mistral 7B v0.2
122
+
123
  The Mistral-7B-v0.2 Large Language Model (LLM) is a pretrained generative text model with 7 billion parameters. Mistral-7B-v0.2 outperforms Llama 2 13B on all benchmarks we tested.
124
 
125
  **Model Intention:** It's a 7B large model for Q&A purpose. But it requires a high-end device to run.
126
 
127
+ **Model URL:** [https://huggingface.co/flyingfishinwater/good_and_small_models/resolve/main/mistral-7b-instruct-v0.2.Q8_0.gguf?download=true](https://huggingface.co/flyingfishinwater/good_and_small_models/resolve/main/mistral-7b-instruct-v0.2.Q8_0.gguf?download=true)
128
 
129
  **Model Info URL:** [https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2)
130
 
 
139
  **Context Length:** 4096 tokens
140
 
141
  **Prompt Format:**
142
+
143
  ```
144
  <s>[INST]{{prompt}}[/INST]</s>
145
+ ```
146
 
147
  **Template Name:** Mistral
148
 
 
156
  ---
157
 
158
  # OpenChat 3.5(0106)
159
+
160
  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.
161
 
162
  **Model Intention:** It's a 7B large model and performs really good for Q&A. But it requires a high-end device to run.
163
 
164
+ **Model URL:** [https://huggingface.co/flyingfishinwater/good_and_small_models/resolve/main/openchat-3.5-0106.Q3_K_M.gguf?download=true](https://huggingface.co/flyingfishinwater/good_and_small_models/resolve/main/openchat-3.5-0106.Q3_K_M.gguf?download=true)
165
 
166
  **Model Info URL:** [https://huggingface.co/openchat/openchat_3.5](https://huggingface.co/openchat/openchat_3.5)
167
 
 
176
  **Context Length:** 8192 tokens
177
 
178
  **Prompt Format:**
179
+
180
  ```
181
  GPT4 Correct User: {{prompt}}<|end_of_turn|>GPT4 Correct Assistant:
182
+ ```
183
 
184
  **Template Name:** Mistral
185
 
 
192
 
193
  ---
194
 
195
+ # Phi-3 4K
196
+
197
+ 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.
198
 
199
+ **Model Intention:** It's a 3B model with 4K context optimized for language understanding, math, code and logical reasoning
200
 
201
+ **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)
202
 
203
+ **Model Info URL:** [https://huggingface.co/microsoft/Phi-3-mini-4k-instruct](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct)
204
 
205
  **Model License:** [License Info](https://opensource.org/license/mit)
206
 
207
+ **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.
208
 
209
+ **Developer:** [https://huggingface.co/microsoft/Phi-3-mini-4k-instruct](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct)
210
 
211
+ **File Size:** 2320 MB
212
 
213
+ **Context Length:** 4096 tokens
214
 
215
  **Prompt Format:**
216
+
217
+ ```
218
+ <|user|>
219
+ {{prompt}} <|end|>
220
+ <|assistant|>
221
  ```
 
 
 
222
 
223
+ **Template Name:** PHI3
224
 
225
  **Add BOS Token:** Yes
226
 
 
232
  ---
233
 
234
  # Yi 6B Chat
235
+
236
  The Yi series models are the next generation of open-source large language models trained from scratch by 01.AI. Targeted as a bilingual language model and trained on 3T multilingual corpus, the Yi series models become one of the strongest LLM worldwide, showing promise in language understanding, commonsense reasoning, reading comprehension, and more. For example, For English language capability, the Yi series models ranked 2nd (just behind GPT-4), outperforming other LLMs (such as LLaMA2-chat-70B, Claude 2, and ChatGPT) on the AlpacaEval Leaderboard in Dec 2023. For Chinese language capability, the Yi series models landed in 2nd place (following GPT-4), surpassing other LLMs (such as Baidu ERNIE, Qwen, and Baichuan) on the SuperCLUE in Oct 2023.
237
 
238
  **Model Intention:** It's a 6B model and can understand English and Chinese. It's good for QA and Chat
239
 
240
+ **Model URL:** [https://huggingface.co/flyingfishinwater/good_and_small_models/resolve/main/yi-chat-6b.Q4_K_M.gguf?download=true](https://huggingface.co/flyingfishinwater/good_and_small_models/resolve/main/yi-chat-6b.Q4_K_M.gguf?download=true)
241
 
242
  **Model Info URL:** [https://huggingface.co/01-ai/Yi-6B-Chat](https://huggingface.co/01-ai/Yi-6B-Chat)
243
 
 
252
  **Context Length:** 4096 tokens
253
 
254
  **Prompt Format:**
255
+
256
  ```
257
  <|im_start|>user
258
  <|im_end|>
259
  {{prompt}}
260
  <|im_start|>assistant
261
 
262
+ ```
263
 
264
  **Template Name:** yi
265
 
 
273
  ---
274
 
275
  # Google Gemma 2B
276
+
277
  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).
278
 
279
  **Model Intention:** It's a 2B large model for Q&A purpose. But it requires a high-end device to run.
280
 
281
+ **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)
282
 
283
  **Model Info URL:** [https://huggingface.co/google/gemma-2b](https://huggingface.co/google/gemma-2b)
284
 
 
293
  **Context Length:** 8192 tokens
294
 
295
  **Prompt Format:**
296
+
297
  ```
298
  <bos><start_of_turn>user
299
  {{prompt}}<end_of_turn>
300
  <start_of_turn>model
301
 
302
+ ```
303
 
304
  **Template Name:** gemma
305
 
 
313
  ---
314
 
315
  # StarCoder2 3B
316
+
317
  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
318
 
319
  **Model Intention:** The model is good at 17 programming languages. By just start with your codes, the model will finish it.
320
 
321
+ **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)
322
 
323
  **Model Info URL:** [https://huggingface.co/bigcode/starcoder2-3b](https://huggingface.co/bigcode/starcoder2-3b)
324
 
 
333
  **Context Length:** 16384 tokens
334
 
335
  **Prompt Format:**
336
+
337
  ```
338
  {{prompt}}
339
 
340
+ ```
341
 
342
  **Template Name:** starcoder
343
 
 
351
  ---
352
 
353
  # Chinese Tiny LLM 2B
354
+
355
  Chinese Tiny LLM 2B 是首个以中文为中心的大型语言模型,主要在中文语料库上进行预训练和微调,提供了对潜在偏见、中文语言能力和多语言适应性的重要洞见。
356
 
357
  **Model Intention:** 这是一个参数规模2B的中文模型,具有很好的中文理解和应答能力
358
 
359
+ **Model URL:** [https://huggingface.co/flyingfishinwater/good_and_small_models/resolve/main/chinese-tiny-llm-2b-Q8_0.gguf?download=true](https://huggingface.co/flyingfishinwater/good_and_small_models/resolve/main/chinese-tiny-llm-2b-Q8_0.gguf?download=true)
360
 
361
  **Model Info URL:** [https://chinese-tiny-llm.github.io/](https://chinese-tiny-llm.github.io/)
362
 
 
371
  **Context Length:** 4096 tokens
372
 
373
  **Prompt Format:**
374
+
375
  ```
376
  <|im_start|>user
377
  {{prompt}}
378
  <|im_end|>
379
  <|im_start|>assistant
380
 
381
+ ```
382
 
383
  **Template Name:** chatml
384
 
 
392
  ---
393
 
394
  # Qwen1.5 4B Chat
395
+
396
  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。
397
 
398
  **Model Intention:** It's one of the best LLM that supports Chinese and English. 这是支持中英双语的最佳的大语言模型之一。
399
 
400
+ **Model URL:** [https://huggingface.co/flyingfishinwater/good_and_small_models/resolve/main/qwen1_5-4b-chat-q4_k_m.gguf?download=true](https://huggingface.co/flyingfishinwater/good_and_small_models/resolve/main/qwen1_5-4b-chat-q4_k_m.gguf?download=true)
401
 
402
  **Model Info URL:** [https://huggingface.co/Qwen/Qwen1.5-4B-Chat-GGUF](https://huggingface.co/Qwen/Qwen1.5-4B-Chat-GGUF)
403
 
 
412
  **Context Length:** 32768 tokens
413
 
414
  **Prompt Format:**
415
+
416
  ```
417
  <|im_start|>user
418
  {{prompt}}
419
  <|im_end|>
420
  <|im_start|>assistant
421
 
422
+ ```
423
 
424
  **Template Name:** chatml
425
 
 
433
  ---
434
 
435
  # Dophin 2.8 Mistralv02 7B
436
+
437
  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.
438
 
439
  **Model Intention:** It's a uncensored and good skilled English modal best for high performance iPhone, iPad & Mac
440
 
441
+ **Model URL:** [https://huggingface.co/flyingfishinwater/good_and_small_models/resolve/main/dolphin-2.8-mistral-7b-v02-Q2_K.gguf?download=true](https://huggingface.co/flyingfishinwater/good_and_small_models/resolve/main/dolphin-2.8-mistral-7b-v02-Q2_K.gguf?download=true)
442
 
443
  **Model Info URL:** [https://huggingface.co/cognitivecomputations/dolphin-2.8-mistral-7b-v02](https://huggingface.co/cognitivecomputations/dolphin-2.8-mistral-7b-v02)
444
 
 
453
  **Context Length:** 32768 tokens
454
 
455
  **Prompt Format:**
456
+
457
  ```
458
  <s><|im_start|>user
459
  {{prompt}}
460
  <|im_end|>
461
  <|im_start|>assistant
462
 
463
+ ```
464
 
465
  **Template Name:** chatml
466
 
 
474
  ---
475
 
476
  # WizardLM-2 7B
477
+
478
  The WizardLM-2 is one of the next generation state-of-the-art large language models, which have improved performance on complex chat, multilingual, reasoning and agent.
479
 
480
  **Model Intention:** It's a state-of-the-art large language model with improved performance on complex chat, multilingual, reasoning and agent.
481
 
482
+ **Model URL:** [https://huggingface.co/flyingfishinwater/good_and_small_models/resolve/main/WizardLM-2-7B.Q3_K_M.gguf?download=true](https://huggingface.co/flyingfishinwater/good_and_small_models/resolve/main/WizardLM-2-7B.Q3_K_M.gguf?download=true)
483
 
484
  **Model Info URL:** [https://huggingface.co/MaziyarPanahi/WizardLM-2-7B-GGUF](https://huggingface.co/MaziyarPanahi/WizardLM-2-7B-GGUF)
485
 
 
494
  **Context Length:** 32768 tokens
495
 
496
  **Prompt Format:**
497
+
498
  ```
499
  A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions.
500
  USER: {{prompt}}
501
  ASSISTANT:
502
+ ```
503
 
504
  **Template Name:** chatml
505
 
 
507
 
508
  **Add EOS Token:** No
509
 
510
+ **Parse Special Tokens:** Yes