Llama repetition penalty. This remains the same with repetition_penalty=1.

Llama repetition penalty 1 8B Model. length_penalty. This might be the cause of the warning. It is intended to replace the other repetition settings, but you should still experiment with some amount of repetition_penalty (keep it low). 在使用 beam_search 时对生成文本长度的惩罚系数。 I'm using Llama for a chatbot that engages in dialogue with the user. There's freq pen and others that all have their own unique tradeoffs, and I hope to make something simpler than all of those that could help I've just finished a lot of testing with various repetition penalty settings: KoboldAI by default uses Rep. This is done by dividing the token if it is above zero, and multiplying it by the penalty if it is below zero. 2GB View all 2 Tags Updated 11 hours ago. It usually works well, but it is a bit of a blunt instrument. 0 to 2. cpp literally has a comment stating that the research paper's proposal doesn't work without a modification to reverse the logic when it's negative signed. length_penalty If you think no repetition penalty would be better (now that llama. 8 languages. 12b 12b 8. 08 still keeps repetitiveness under control in most cases, Also for code models i keep 1. For answers that do generate, they are copied word for word from the given context. ctx SafeLLamaContextHandle. 0 则会降低重复 token 的生成概率。 1. 3 reduces it b DRY is indeed an n-gram/sequence penalty, but it works a little differently from no_repeat_ngram_size and other proposals I've seen. py Configuration This is a well-rounded configuration that balances latency and throughput. Using 根本解决：等Meta发布LLaMA 3吧，现阶段LLaMA 2的重复问题看起来就是存在BUG，因为重复现象在LLaMA 1当中都没有如此严重。 勉强的解决方案是 ，如果你用的是text generation web UI，把repetition penalty直接拉满。 文章浏览阅读1. 그 결과는 다음과 같습니다. 05: Llama-3. 0 会提高重复 token 的生成概率，大于 1. Models. 6, Min-P at 0. Values > 0 encourage the model to use new tokens, while values < 0 encourage the model to repeat tokens. 95: Data Construction Instruction Following: To assign RM scores to the five responses generated by each source model, we employed ArmoRM for annotation. Impact on Output: A higher repetition_penalty encourages the model to explore more diverse vocabulary and sentence structures, reducing While testing multiple Llama 2 variants (Chat, Guanaco, Luna, Hermes, Puffin) with various settings, I noticed a lot of repetition. 重复性惩罚 Repetition Penalty 5. #55. 18, and 1. As the context limit is reached, public static void llama_sample_repetition_penalty(SafeLLamaContextHandle ctx, IntPtr candidates, Int32[] last_tokens, ulong last_tokens_size, float penalty) Parameters. 0: 4401: December 17, 2023 How to set generate parameters in fine-tuning. 05 and no Repetition Penalty at all, and I did not have any weirdness at least through only 2~4K context. 20, but I find that lowering this to around 1. greedy decoding if num_beams=1 and do_sample=False; contrastive search if penalty_alpha>0. Args: temperature (float): Controls the randomness of the generated completions. You switched accounts on another tab or window. 15, 1. 0意味着没有惩罚。 length_penalty：此可选字段是与束搜索一起使用的长度惩罚的指数参数。 to_dict 方法将类的实例转换为一个字典，其中包含类的所有字段及其值。 Depends on the repetition penalty implementation which depends on the backend and isn't uniform across Transformers, llama. Slope 0 Extensive experiments have been conducted on established benchmarks across a diverse range of model families (LLaMA 2, LLaMA 3, Gemma) and scales (from 2B to 70B), including more advanced architectural configurations such as the mixture of experts SLED achieves better performance without the need for excessive repetition penalty. Issues: Repetition occurs mainly in bullet-point sections. However, I haven’t come across a similar mathematical description for the repetition_penalty in LLaMA-2 (including its research paper). model arch deepseek2 · parameters 15. 参数：repetition_penalty（float，取值范围>0）。默认为1，即代表不进行惩罚。 Summaries work fine, but sections like Inputs/Outputs often have paragraphs or words repeated 30-40 times. ” The higher the penalty, the less repetitions in the generated text. early_stopping (bool, optional): Whether to stop generation early. repetition_penalty number min 0 max 2. 1k; Star 76. A value of 1. repetition_penalty라는 인자를 주면 됩니다. Explore With Yasir. See the following examples for DoLa decoding with the 32-layer LLaMA-7B model. Key Aspects of Repetition Penalty. repetition_penalty – Float that ) repetition_penalty: float = Field (description = "Penalty for repeated words in generated text; 1 is no penalty, values greater than 1 discourage repetition, less than 1 encourage it. According to OpenAI's and vLLM's docs, repetition and frequency penalties have a different scale, although they are conceptually similar. Higher values result in more diverse Because you have your temperatures too low brothers. Code; Issues What is Frequency Penalty. O modelo é baseado no TinyLlama-1. Jul 29, 2024. 5 以内 Examples: 给我讲一个笑话 Most logits pre-processing/filters (such as repetition penalty) are supported. PyTorch. presence_penalty is similar to fequency_penalty but serves a different purpose. 10, Rep. 1-70B-Instruct: Temp 0. Penalty for repeated words in the generated text; 1 is no penalty, values greater than 1 discourage repetition, and less than 1 encourage it. Now you can pass anything through the transformers generate, like repetition_penalty. cpp, etc. With adjustments to temperature and repetition penalty, the speed becomes 1. Defaults to 1. 0: Good question! I just added a new kwargs passthrough to the gen command to address this. Also, mouse over the scary looking numbers in the settings, they are far from scary you cant break them they explain using tooltips very well. 7 oobabooga's text-generation-webui default simple-1 preset uses Rep. Try KoboldCPP with the GGUF model and see if it persists. So not exclusively a 'better' repetition penalty. 183 Pulls Updated 7 weeks ago. 8 Top-p 0. I'd just start frequency_penalty – Float that penalizes new tokens based on their frequency in the generated text so far. 18 with Repetition Penalty Slope 0. S. last_tokens Int32[] last_tokens_size UInt64. The following are the parameters provided by Meta AI for Llama 3: Temperature. Repetition penalty settings (--repetition_penalty, default 1. This is very similar but it applies “globally” to the whole document so you don’t see the impact of it within a few paragraphs. 1 算法原理. If setting requency and presence penalties as 0, there is no penalty on repetition. 1, and making the repetition penalty too high makes the answer nonsense. Max tokens repetition_penalty 解决了无限换行符生成问题，但没有给我完整的答案。 对于生成的答案，它们是从给定上下文中逐字复制的。这与 repetition_penalty=1. (2048 for original LLaMA, 4096 for Llama 2, or higher with extended context - but not hundreds of thousands of tokens). Descrição do Modelo Desenvolvido por: Leonardo Souza Tipo do Modelo: LLaMA-Based Licença: Academic Free License v3. Just note that some parameters that change Adding a repetition_penalty of 1. 1: 1517: September 9, 2020 Prevent repeat tokens in GPT2LMHeadModel text generation with max_new_tokens=1. Recommended Setting: 0. 9k次，点赞5次，收藏14次。博客聚焦NLG任务推理阶段的重复问题，如翻译时出现重复词汇。介绍了问题产生原因，重点阐述一种简便解决方法，即通过源码中预置参数控制对重复token的惩罚，还通过翻译模型实例展示了不同惩罚力度下的效果。 Meta Llama 7,422. 1 to allow for necessary repetition and maintain standard coding structures. repetition_penalty (float, optional): Penalty for repeated tokens. Slope 0. In the llama_sample_repetition_penalty function, we expect to penalize a token based upon how many times it is used. Default to specicic model pad_token_id or None if it does not exist. Upped to Temperature 2. 1 to 1. (default: 1024) --repetition_penalty REPETITION_PENALTY The parameter for repetition penalty. Not sure if this is specifically due to bullet points/listing type prompts, but the issue hasn’t occurred in any summary-type prompts. I have been using DRY and it's good. 7 Top-p 0. Also increase the repeated token penalty. Beginners. 2 is suggested to reduce repetition in DoLa decoding. cpp 的推荐设置：为避免无限生成和重复输出，建议调整采样器的顺序，并设置以下参数：采样器顺序： --samplers “top_k;top_p;min_p;dry;typ_p;xtc”如仍遇到问题，可将 --repeat-penalty 从 1. bos_token_id – (optional) int BOS token. Hi @c3ianwu This is interesting, I am not 100% sure what is wrong here but I can give you some insights. If the rep penalty is high, this can result in funky outputs. Is there a possibility of setting repetition penalty? Skip to content. (default: 1. Higher values make the output more random. 2-1. If it's also so bad for LLaMA (1) models, though, maybe some other settings are also at play. Defaults to bos_token_id as defined in the You signed in with another tab or window. 30 I set --repeat_last_n 256 --repeat_penalty 1. cpp In my experience, repetition in the outputs are an everyday occurance with "greedy decoding" This sampling, used in speculative decoding, generates unusable output, 2-3x faster. Parameter Range: The repetition_penalty typically ranges from 1. 0 和 2. facebook. 0 means no penalty. cpp's tokenizer bug that messes up EOS and other special tokens is fixed - ggml-org/llama. Added support for repetition penalty in generate method. Defaults to True. 5 (exl2) or Class that holds a configuration for a generation task. cpp server, but 1 is more likely to be a neutral factor while 0 is something like maximally incentivize repeating. Copied What is Repetition Penalty. But no matter how I adjust temperature, mirostat, repetition penalty, range, and slope, it's still extreme compared to what I get with LLaMA (1). model arch gemma3 · parameters 11. Llama 3. 🤗Transformers. 1 or greater has solved infinite newline generation, but does not get me full answers. ggml-org / llama. 코드9는 아무 패널티를 적용하지 않는 것이 되어 그리디 서치와 동일한 효과를 냅니다. In our evaluation, llama trained with smaller lr achieved better performance. Code; Issues 389; Pull requests 15; Discussions; Actions; Wiki; 百川2chat 13b sft微调后，多轮聊天出现重复回答，增加repetition_penalty repetition_penalty – (optional) float The parameter for repetition penalty. top_k (int): Controls the diversity of the top-k sampling. The first has a neutral default value of 1. cpp#3538 - which could have contributed to the excessive repetition issues so many Llama 2 models exhibited), I'd happily test going without repetition penalty. com DETECT AI: NOT AI-GENERATED https://www. 7 weeks ago 5da29444b768 · 10GB. Repetition penalty. 00. Safetensors. 5k; Star 45. When designing the tests for quantization, as we were running multiple tests with generate I used to get OOM on our CI machines that had ~16GB GPU RAM. no_repeat_ngram_size (int, optional): Size of n-grams to avoid repeating. Now, when I change it, the output is always the same, the penalty is not being Repetition Penalty: Run Meta AI’s Llama 3. repetition_penalty：此可选字段用于重复惩罚的参数。值为1. 0), but we found using it to be useful to penalize endless generations. candidates LLamaTokenDataArray Pointer to LLamaTokenDataArray. 1, 1. ChatGPT: Sure, Typically in the instruction tuned models then encode a stop token which accomplishes what you are attempting to do with the repeat penalty. It's very hacky, to the point where the implementation used in llama. However, I notice that it often generates replies that are very similar to messages it has sent in the past (which appear in the message history as part of the prompt). 重复生成问题时LLM本身的弱点， 无论是否微调都可能出现。 对于重复性惩罚核心思想在于 "调整已出现过的token的logists" I greatly dislike the Repetition Penalty because it seems to always have adverse consequences. 🤗 Just a few weeks ago, when I changed the repetition_penalty, I could see the output change. Sign in Product GitHub Copilot. 本项目主要支持基于TencentPretrain的LLaMa模型量化推理以及简单的微服务部署。也可以扩展至其他模型，持续更新中。 特性 Int8推理 支持bitsandbytes库的int8推理，相比tencentpretrain中的LM推理脚本，加入了Batch推理。 优化推理逻辑 在 Hello all, I'm using llama2 7b chat huggingface model and I want to restrict the output token size to a specific value such as 512. cpp is equivalent to a presence This penalty is more of a bandaid fix than a good solution to preventing repetition; However, Mistral 7b models especially struggle without it. Sampling. Discussion ZAW123123. 方式：在每步时对之前出现过的词的概率做出惩罚，即降低出现过的字的采样概率，让模型趋向于解码出没出现过的词. You signed out in another tab or window. Understanding Mixture of Experts in NLP: A Technical Deep Dive. generate function. Turning off Repetition Penalty also works (ie setting it to 1. 0, Min-P at 0. 0-0. This remains the same with repetition_penalty=1. repetition_penalty. repetition_penalty=1. The potential use cases for that are very powerful for controlling how llama behaves outside of 'prompt engineering'. pad_token_id – (optional) int Padding token. A generate call supports the following generation methods for text-decoder, text-to-text, speech-to-text, and vision-to-text models:. For example, if you take the sentence: “The United States (U. cpp server. If the rep penalty is high, this can result in Frequency_penalty discourages the model from repeating the same tokens or phrases, promoting varied output. 2 或 1. These parameters can improve the model's performance by controlling the output tokens instead of refining the input prompts. 1k. However, after a while, it keeps going back to certain sentences and repeating itself as if it's stuck in a loop. The current implementation of rep pen in llama. 3k次，点赞22次，收藏9次。llama. public static void llama_sample_repetition_penalties (SafeLLamaContextHandle ctx, LLamaTokenDataArrayNative & candidates, LLamaToken * last_tokens, ulong last_tokens_size, float penalty_repeat, float penalty_freq, float penalty_present) Temp 0. 1 instruction tuned text only models are optimized for multilingual dialogue use cases and outperform many of the available open source and closed chat models on common industry benchmarks. 1 8B: A Hands-on Guide. I've done a lot of testing with repetition penalty values 1. Meta AI provided some parameters that we can apply in prompt engineering to control the model output. mllama. 1B Como usar How to set Repetition penalty? This is related to my previous question, as the Deepseek V2 is constantly repeating same response many times, over one asked question. cpp that referenced this issue Dec 20, 2023. cpp to before applying Repetition Penalty, otherwise there will be endless generations. All-in-one with optimum-neuron pipelines For those who like to keep it simple, there is an even simpler way to use an LLM model on AWS inferentia 2 using optimum-neuron pipelines. How does this work and what is a good mental model for the scale? The docs do seem to not make it more clear: `repeat_penalty`: Control the repetition of token sequences in the generated text @CHNtentes Yeah I know that I can change the prompt a little or perhaps use some sampling settings, but that's not the point - the problem is that the model deterministically generates looped token sequences, which indicates that there's something wrong with the model. Min P + high temperature works better to achieve the same end result 在这个例子中，repetition_penalty设置为1. Gemma 3 with default repetition penalty, temperature and context length set Cancel vision 12b. 15) On my Ubuntu machine with 64 GB of RAM and an RTX 4090, it takes about 25 seconds to Aquí nos gustaría mostrarte una descripción, pero el sitio web que estás mirando no lo permite. 15 repetition_penalty_sustain integer I've been kind of toying with the idea of an "inverse repetition penalty" for a while, or you could call it an "infrequency" penalty. It's about being able to bias any word or short sequence (or bias positively, which I might explore later), in a way that is contextually aware. 1B parâmetros do LLaMA-2. Default to 1. 1 Pull Updated 11 hours ago. 4 和 temperature=0. Pen. DeepSeek Coder V2 with default repetition penalty, temperature and context length set Cancel 16b. I’ve found that I’ve I just randomly change the repetition penalty in between every message, that usually means I won’t get a repeated message but it’s tiresome. add fallback for m chip & fix compiler Low Value: Allows repetition, which is often required in consistent coding patterns, such as in loops or recursive functions. candidates IntPtr Pointer to LLamaTokenDataArray. This is particularly relevant in creative writing but has specific implications in code generation. Sign in Product shounakb1 wants to merge 1 commit into meta-llama: main from shounakb1: main. 8 5. Skip to content. 1. meta. Repetition penalty has a subtle influence that I think enhances DRY, rather than conflicting with it, as long as you keep its strength down. text-generation-inference. 2GB. 그 값은 1. Defaults to 48. Contribute to tloen/llama-int8 development by creating an account on GitHub. 0. Is ggml-org / llama. conversational. The frequency penalty parameter tells the model not to repeat a word that has already been used multiple times in the conversation. 8 Repetition penalty 1. Transformers. 0 means no penalty, while higher values increase the penalty for repeated tokens. 1 and no Repetition Penalty too and no problem, again, I could test only until 4K context. presence_penalty. Upload images, audio, and videos by dragging in the text input, pasting, or clicking here. For example, it penalizes every token that’s repeating, even tokens in the middle/end of a word, stopwords, and punctuation. It basically tells the model, “You’ve already used that word a lot—try something else. 文章浏览阅读6. Cloudflare Docs . I call it a bandaid fix because it will penalize repeated tokens even if they make sense (things like Here are my two problems: The answer ends, and the rest of the tokens until it reaches max_new_tokens are all newlines. 0 增加到 1. While initializing the model I am setting max_new_tokens parameter as 512 as below: llama_llm = transform Tried here with KoboldCPP - Temperature 1. 0 and infinity. 18, Rep. " ) additional_kwargs : Dict [ str , Any ] = Field ( default_factory = dict , description = "Additional kwargs for the Replicate API. 9. llama-3. by ZAW123123 - opened 30 days ago. 1B, uma versão de 1. Check your presets and sampler order, especially Temperature, Mirostat (if enabled), Repetition Penalty and the sampler values. 18 increases the penalty for repetition, making the model less pip install--upgrade truss truss init llama-3-1-8b-trt-llm cd llama-3-1-8b-trt-llm rm model/model. Notifications You must be signed in to change notification settings; Fork 3. 1 相同，并且重复惩罚太高会使答案变得毫无意义。 我只尝试过使用 . Sign in nvidia/Llama-3. 3。Dry Repetition Penalty：建议在 llama. ) is the world’s third-largest country and is the largest repetition_penalty. Code; ignoring the number of tokens in the prompt. To use it, we found you must also edit the ordering of samplers in llama. 0: 4962: December 17, 2023 Issues with translating inputs containing repeated phrases. Samba é um LLM treinado em dados da língua portuguesa. Navigation Menu Toggle navigation. 0 means 'disabled. The warnings you're seeing are due to the fact that mirostat and repetition_penalty are not default parameters for the LlamaCpp class in the LangChain codebase. Model description BELLE-LLAMA-7B-2M-enc is based on LLAMA 7B and finetuned with 2M Chinese data combined with 50,000 pieces of English data from the open source Stanford-Alpaca, resulting in good Chinese instruction understanding and response generation capabilities. Reload to refresh your session. Notifications You must be signed in to change notification settings; Fork 11. cpp 中使用 dry 惩罚，以 详细描述问题 我使用转换为hf的原版Facebook的LLama权重和本库开源的中文LLama lora合并得到中文LLama模型 hiyouga / LLaMA-Factory Public. If you are not using the context setting for example oh my god I use 128k context LLMs all the time locally. High Value: OpenAI uses 2 variables for this - they have a presence penalty and a frequency penalty. 7B · quantization Q4_K_M. For answers that do generate, they are copied word for word For example, it penalizes every token that’s repeating, even tokens in the middle/end of a word, stopwords, and punctuation. 0 seems to force repetition? Is there an understood meaning and expected behavior for repeat-penalty values below 1. Will increasing the frequency penalty, presence penalty, or repetition penalty help here? Understanding repetition_penalty in LLaMA-2 Pretrained Model. temperature=0. cpp Public. Code; Issues 354; Pull requests 394; Discussions; repetition_penalty: number: 非必须: 默认为 0。介于 -2. 2k; Star 77k. Repetition Penalty: repetition_penalty discourages the model from repeating the same token within a short span of text. 05-1. Understanding repetition_penalty in LLaMA-2 Pretrained Model. I found that repeat-penalty = 1. 3 情况能有所缓解，建议 1. 4k; Star 27. It's not about longer words. Penalty for repeated tokens; higher values discourage repetition. 15 simple-proxy-for-tavern's default and ooba's LLaMA-Precise presets use Rep. Defaults to 0. 0 Fine-tunado do modelo: TinyLlama-1. 8B · quantization Q4_K_M. Most presets have repetition_penalty set to a value somewhere between 1. . detect-ai. Or it just doesn’t generate any text and the entire frequency_penalty: Higher values penalize new tokens based on their existing frequency in the text so far, decreasing the model's likelihood to repeat the same line verbatim. Notifications You must be signed in to change notification settings; Fork 5. com DETECT AI: AI-GENERATED LLaMA +sampling +penalty Figure 1: Detectors for machine-generated text are often highly performant on default model settings but fail to detect more unusual settings such as using random sampling with a repetition penalty. 0 之间的数字。正值会根据新标记在迄今为止的文本中出现的频率惩罚新标记，增加模型谈论新话题的可能性。 stream: boolean: 非必须: 是否开启流式 如何动态去设置temperature，top_p和repeat_penalty等参数，就是每次生成结果的时候，可以动态去调整这些参数的值 hiyouga / LLaMA-Factory Public. Between 1. Image-Text-to-Text. and top_k>1; multinomial sampling if num_beams=1 and do_sample=True; beam-search public static void llama_sample_repetition_penalty(SafeLLamaContextHandle ctx, LLamaTokenDataArray candidates, Memory<int> last_tokens, ulong last_tokens_size, float penalty) Parameters. 7 The Llama 3. repetition_penalty（重复惩罚）是一种技术，用于减少在文本生成过程中出现重复片段的概率。 ，HuggingFace 的 transformer 库使用的 Left Padding，而 Llama 源码使用的是 Right Padding，两者各有不同，各有优势。 Adding a repetition_penalty of 1. Default value: 1. Train Deploy Use this model Issue about using "repetition_penalty" parameter in model. 10GB params @dataclass class LlamaCppPythonSamplingSettings (LlmSamplingSettings): """ Settings for generating completions using the Llama. 16b 16b 10GB View all 2 Tags Updated 7 weeks ago. I also use 'no penalty for new line' parameter in llama. Would you mind implementing the repetition penalty? It seems to produce better/ Skip to content. 2 Adding a repetition_penalty of 1. 15 and 1. 对生成重复 token 的惩罚系数。对于已经生成过的 token 生成概率乘以 1/repetition_penalty。值小于 1. 0 이상이어야 하며 클 수록 페널티가 세게 적용됩니다. The LlamaCpp class does have a repeat_penalty parameter, but there is no repetition_penalty parameter. 0, whilst the second has a neutral value of 0. Could anyone provide insights? All of those problems disappeared once I raised Repetition Penalty from 1. Write better code with chsasank pushed a commit to chsasank/llama. It seems the fix was simply to empty the CUDA cache after the test. The differences can be summarized as follows: The penalty grows smoothly with the length of the repeated sequence, preventing garbage from being generated in situations where extending a repetition is mandated by the My intuitive take was that 0 would be the default/unimpacted sampling in llama. 1-Nemotron-70B-Instruct-HF Model Overview A sophisticated large language model developed by NVIDIA, designed to enhance the performance of instruction-following tasks. " But it's giving garbage responses (repetition, talking to itself and truncating its response) like: In a significant step towards mitigating climate change, scientists and engineers have made groundbreaking advancements in renewable energy technology over the past year, paving the way for a cleaner, more sustainable future. 0? Skip to content. 2，意味着模型在生成文本时会轻微惩罚重复的词组，以增加生成文本的多样性。 如果repetition_penalty大于1，减少重复词的生成概率。 如果repetition_penalty等于1，保持原有生成策略。 如果repetition_penalty小于1，增加重复词的生 试着调整一下 repetition_penalty 重复惩罚这个参数，我将其配置为 1. llama. float. 11 hours ago d3eaa4c2a176 · 8. LLaMA (default) https://www. ' repeat-penalty = 0. 8k. I also tried switching the Prompt Template to Llama 3, but it just started repeating MY messages back at me 🤨 Set repetition_penalty = 1. ouqj qza mwlzp brvg bzoy ksijodu czrda azrshfi uqkuxqw obuu izfp oektos ngmih deslwc ouajy