From 8155fa3a39703d960fc09f458bea294b55cc59f4 Mon Sep 17 00:00:00 2001 From: ModelHub XC Date: Tue, 8 Sep 2026 08:58:16 +0800 Subject: [PATCH] =?UTF-8?q?=E5=88=9D=E5=A7=8B=E5=8C=96=E9=A1=B9=E7=9B=AE?= =?UTF-8?q?=EF=BC=8C=E7=94=B1ModelHub=20XC=E7=A4=BE=E5=8C=BA=E6=8F=90?= =?UTF-8?q?=E4=BE=9B=E6=A8=A1=E5=9E=8B?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Model: hermes42/Phi-3-medium-128k-instruct-imatrix-GGUF Source: Original Platform --- .gitattributes | 68 +++ Phi-3-medium-128k-instruct-imatrix-IQ1_M.gguf | 3 + Phi-3-medium-128k-instruct-imatrix-IQ1_S.gguf | 3 + Phi-3-medium-128k-instruct-imatrix-IQ2_M.gguf | 3 + Phi-3-medium-128k-instruct-imatrix-IQ2_S.gguf | 3 + ...3-medium-128k-instruct-imatrix-IQ2_XS.gguf | 3 + ...-medium-128k-instruct-imatrix-IQ2_XXS.gguf | 3 + Phi-3-medium-128k-instruct-imatrix-IQ3_M.gguf | 3 + Phi-3-medium-128k-instruct-imatrix-IQ3_S.gguf | 3 + ...3-medium-128k-instruct-imatrix-IQ3_XS.gguf | 3 + 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you provide ways to eat combinations of bananas and dragonfruits? +--- +GGUF quants of https://huggingface.co/microsoft/Phi-3-medium-128k-instruct with importance matrix calculations run on group_10_merged.txt for improved perplexity. +Quantified with llama.cpp as of commitid 03d8900ebe062355e26a562379daee5f17ea099f from 2024-05-22 + +Orinal README below: + +## Model Summary + +The Phi-3-Medium-128K-Instruct is a 14B parameters, lightweight, state-of-the-art open model trained with the Phi-3 datasets that includes both synthetic data and the filtered publicly available websites data with a focus on high-quality and reasoning dense properties. +The model belongs to the Phi-3 family with the Medium version in two variants [4k](https://huggingface.co/microsoft/Phi-3-medium-4k-instruct) and [128K](https://huggingface.co/microsoft/Phi-3-medium-128k-instruct) which is the context length (in tokens) that it can support. + +The model has underwent a post-training process that incorporates both supervised fine-tuning and direct preference optimization for the instruction following and safety measures. +When assessed against benchmarks testing common sense, language understanding, math, code, long context and logical reasoning, Phi-3-Medium-128K-Instruct showcased a robust and state-of-the-art performance among models of the same-size and next-size-up. + +Resources and Technical Documentation: + ++ [Phi-3 Microsoft Blog](https://aka.ms/Phi-3Build2024) ++ [Phi-3 Technical Report](https://aka.ms/phi3-tech-report) ++ [Phi-3 on Azure AI Studio](https://aka.ms/phi3-azure-ai) ++ [Phi-3 Cookbook](https://github.com/microsoft/Phi-3CookBook) + +| | Short Context | Long Context | +| ------- | ------------- | ------------ | +| Mini | 4K [[HF]](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct) ; [[ONNX]](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct-onnx) ; [[GGUF]](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct-gguf) | 128K [[HF]](https://huggingface.co/microsoft/Phi-3-mini-128k-instruct) ; [[ONNX]](https://huggingface.co/microsoft/Phi-3-mini-128k-instruct-onnx)| +| Small | 8K [[HF]](https://huggingface.co/microsoft/Phi-3-small-8k-instruct) ; [[ONNX]](https://huggingface.co/microsoft/Phi-3-small-8k-instruct-onnx-cuda) | 128K [[HF]](https://huggingface.co/microsoft/Phi-3-small-128k-instruct) ; [[ONNX]](https://huggingface.co/microsoft/Phi-3-small-128k-instruct-onnx-cuda)| +| Medium | 4K [[HF]](https://huggingface.co/microsoft/Phi-3-medium-4k-instruct) ; [[ONNX]](https://huggingface.co/microsoft/Phi-3-medium-4k-instruct-onnx-cuda) | 128K [[HF]](https://huggingface.co/microsoft/Phi-3-medium-128k-instruct) ; [[ONNX]](https://huggingface.co/microsoft/Phi-3-medium-128k-instruct-onnx-cuda)| +| Vision | | 128K [[HF]](https://huggingface.co/microsoft/Phi-3-vision-128k-instruct)| + +## Intended Uses + +**Primary use cases** + +The model is intended for broad commercial and research use in English. The model provides uses for general purpose AI systems and applications which require : + +1) Memory/compute constrained environments +2) Latency bound scenarios +3) Strong reasoning (especially code, math and logic) + +Our model is designed to accelerate research on language and multimodal models, for use as a building block for generative AI powered features. + +**Use case considerations** + +Our models are not specifically designed or evaluated for all downstream purposes. Developers should consider common limitations of language models as they select use cases, and evaluate and mitigate for accuracy, safety, and fariness before using within a specific downstream use case, particularly for high risk scenarios. Developers should be aware of and adhere to applicable laws or regulations (including privacy, trade compliance laws, etc.) that are relevant to their use case. + +Nothing contained in this Model Card should be interpreted as or deemed a restriction or modification to the license the model is released under. + +## How to Use + +Phi-3-Medium-128k-Instruct has been integrated in the development version (4.40.2) of `transformers`. Until the official version is released through `pip`, ensure that you are doing one of the following: +* When loading the model, ensure that `trust_remote_code=True` is passed as an argument of the `from_pretrained()` function. + +* Update your local `transformers` to the development version: `pip uninstall -y transformers && pip install git+https://github.com/huggingface/transformers`. The previous command is an alternative to cloning and installing from the source. + +The current `transformers` version can be verified with: `pip list | grep transformers`. + +Phi-3-Medium-128k-Instruct is also available in [Azure AI Studio](https://aka.ms/phi3-azure-ai). + +### Tokenizer + +Phi-3-Medium-128k-Instruct supports a vocabulary size of up to `32064` tokens. The [tokenizer files](https://huggingface.co/microsoft/Phi-3-medium-128k-instruct/blob/main/added_tokens.json) already provide placeholder tokens that can be used for downstream fine-tuning, but they can also be extended up to the model's vocabulary size. + +### Chat Format + +Given the nature of the training data, the Phi-3-Medium-128k-Instruct model is best suited for prompts using the chat format as follows. +You can provide the prompt as a question with a generic template as follow: +```markdown +<|user|>\nQuestion <|end|>\n<|assistant|> +``` +For example: +```markdown +<|user|> +How to explain Internet for a medieval knight?<|end|> +<|assistant|> +``` + +where the model generates the text after `<|assistant|>` . In case of few-shots prompt, the prompt can be formatted as the following: + +```markdown +<|user|> +I am going to Paris, what should I see?<|end|> +<|assistant|> +Paris, the capital of France, is known for its stunning architecture, art museums, historical landmarks, and romantic atmosphere. Here are some of the top attractions to see in Paris:\n\n1. The Eiffel Tower: The iconic Eiffel Tower is one of the most recognizable landmarks in the world and offers breathtaking views of the city.\n2. The Louvre Museum: The Louvre is one of the world's largest and most famous museums, housing an impressive collection of art and artifacts, including the Mona Lisa.\n3. Notre-Dame Cathedral: This beautiful cathedral is one of the most famous landmarks in Paris and is known for its Gothic architecture and stunning stained glass windows.\n\nThese are just a few of the many attractions that Paris has to offer. With so much to see and do, it's no wonder that Paris is one of the most popular tourist destinations in the world."<|end|> +<|user|> +What is so great about #1?<|end|> +<|assistant|> +``` + +### Sample inference code + +This code snippets show how to get quickly started with running the model on a GPU: + +```python +import torch +from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline + +torch.random.manual_seed(0) +model_id = "microsoft/Phi-3-medium-128k-instruct" +model = AutoModelForCausalLM.from_pretrained( + model_id, + device_map="cuda", + torch_dtype="auto", + trust_remote_code=True, +) +tokenizer = AutoTokenizer.from_pretrained(model_id) + +messages = [ + {"role": "user", "content": "Can you provide ways to eat combinations of bananas and dragonfruits?"}, + {"role": "assistant", "content": "Sure! Here are some ways to eat bananas and dragonfruits together: 1. Banana and dragonfruit smoothie: Blend bananas and dragonfruits together with some milk and honey. 2. Banana and dragonfruit salad: Mix sliced bananas and dragonfruits together with some lemon juice and honey."}, + {"role": "user", "content": "What about solving an 2x + 3 = 7 equation?"}, +] + +pipe = pipeline( + "text-generation", + model=model, + tokenizer=tokenizer, +) + +generation_args = { + "max_new_tokens": 500, + "return_full_text": False, + "temperature": 0.0, + "do_sample": False, +} + +output = pipe(messages, **generation_args) +print(output[0]['generated_text']) +``` + +*Some applications/frameworks might not include a BOS token (``) at the start of the conversation. Please ensure that it is included since it provides more reliable results.* + +## Responsible AI Considerations + +Like other language models, the Phi series models can potentially behave in ways that are unfair, unreliable, or offensive. Some of the limiting behaviors to be aware of include: + ++ Quality of Service: the Phi models are trained primarily on English text. Languages other than English will experience worse performance. English language varieties with less representation in the training data might experience worse performance than standard American English. ++ Representation of Harms & Perpetuation of Stereotypes: These models can over- or under-represent groups of people, erase representation of some groups, or reinforce demeaning or negative stereotypes. Despite safety post-training, these limitations may still be present due to differing levels of representation of different groups or prevalence of examples of negative stereotypes in training data that reflect real-world patterns and societal biases. ++ Inappropriate or Offensive Content: these models may produce other types of inappropriate or offensive content, which may make it inappropriate to deploy for sensitive contexts without additional mitigations that are specific to the use case. ++ Information Reliability: Language models can generate nonsensical content or fabricate content that might sound reasonable but is inaccurate or outdated. ++ Limited Scope for Code: Majority of Phi-3 training data is based in Python and use common packages such as "typing, math, random, collections, datetime, itertools". If the model generates Python scripts that utilize other packages or scripts in other languages, we strongly recommend users manually verify all API uses. + +Developers should apply responsible AI best practices and are responsible for ensuring that a specific use case complies with relevant laws and regulations (e.g. privacy, trade, etc.). Important areas for consideration include: + ++ Allocation: Models may not be suitable for scenarios that could have consequential impact on legal status or the allocation of resources or life opportunities (ex: housing, employment, credit, etc.) without further assessments and additional debiasing techniques. ++ High-Risk Scenarios: Developers should assess suitability of using models in high-risk scenarios where unfair, unreliable or offensive outputs might be extremely costly or lead to harm. This includes providing advice in sensitive or expert domains where accuracy and reliability are critical (ex: legal or health advice). Additional safeguards should be implemented at the application level according to the deployment context. ++ Misinformation: Models may produce inaccurate information. Developers should follow transparency best practices and inform end-users they are interacting with an AI system. At the application level, developers can build feedback mechanisms and pipelines to ground responses in use-case specific, contextual information, a technique known as Retrieval Augmented Generation (RAG). ++ Generation of Harmful Content: Developers should assess outputs for their context and use available safety classifiers or custom solutions appropriate for their use case. ++ Misuse: Other forms of misuse such as fraud, spam, or malware production may be possible, and developers should ensure that their applications do not violate applicable laws and regulations. + + +## Training + +### Model + +* Architecture: Phi-3-Medium-128k-Instruct has 14B parameters and is a dense decoder-only Transformer model. The model is fine-tuned with Supervised fine-tuning (SFT) and Direct Preference Optimization (DPO) to ensure alignment with human preferences and safety guidlines. +* Inputs: Text. It is best suited for prompts using chat format. +* Context length: 128k tokens +* GPUs: 512 H100-80G +* Training time: 42 days +* Training data: 4.8T tokens +* Outputs: Generated text in response to the input +* Dates: Our models were trained between February and April 2024 +* Status: This is a static model trained on an offline dataset with cutoff date October 2023. Future versions of the tuned models may be released as we improve models. +* Release dates: The model weight is released on May 21, 2024. + +### Datasets + +Our training data includes a wide variety of sources, totaling 4.8 trillion tokens (including 10% multilingual), and is a combination of +1) Publicly available documents filtered rigorously for quality, selected high-quality educational data, and code; +2) Newly created synthetic, “textbook-like” data for the purpose of teaching math, coding, common sense reasoning, general knowledge of the world (science, daily activities, theory of mind, etc.); +3) High quality chat format supervised data covering various topics to reflect human preferences on different aspects such as instruct-following, truthfulness, honesty and helpfulness. + +We are focusing on the quality of data that could potentially improve the reasoning ability for the model, and we filter the publicly available documents to contain the correct level of knowledge. As an example, the result of a game in premier league in a particular day might be good training data for frontier models, but we need to remove such information to leave more model capacity for reasoning for the small size models. More details about data can be found in the [Phi-3 Technical Report](https://aka.ms/phi3-tech-report). + +## Benchmarks + +We report the results for Phi-3-Medium-128k-Instruct on standard open-source benchmarks measuring the model's reasoning ability (both common sense reasoning and logical reasoning). We compare to Mixtral-8x22b, Gemini-Pro, Command R+ 104B, Llama-3-70B-Instruct, GPT-3.5-Turbo-1106, and GPT-4-Turbo-1106(Chat). + +All the reported numbers are produced with the exact same pipeline to ensure that the numbers are comparable. These numbers might differ from other published numbers due to slightly different choices in the evaluation. + +As is now standard, we use few-shot prompts to evaluate the models, at temperature 0. +The prompts and number of shots are part of a Microsoft internal tool to evaluate language models, and in particular we did no optimization to the pipeline for Phi-3. +More specifically, we do not change prompts, pick different few-shot examples, change prompt format, or do any other form of optimization for the model. + +The number of k–shot examples is listed per-benchmark. + +|Benchmark|Phi-3-Medium-128k-Instruct
14b|Command R+
104B|Mixtral
8x22B|Llama-3-70B-Instruct|GPT3.5-Turbo
version 1106|Gemini
Pro|GPT-4-Turbo
version 1106 (Chat)| +|---------|-----------------------|--------|-------------|-------------------|-------------------|----------|------------------------| +|AGI Eval
5-shot|49.7|50.1|54.0|56.9|48.4|49.0|59.6| +|MMLU
5-shot|76.6|73.8|76.2|80.2|71.4|66.7|84.0| +|BigBench Hard
3-shot|77.9|74.1|81.8|80.4|68.3|75.6|87.7| +|ANLI
7-shot|57.3|63.4|65.2|68.3|58.1|64.2|71.7| +|HellaSwag
5-shot|81.6|78.0|79.0|82.6|78.8|76.2|88.3| +|ARC Challenge
10-shot|91.0|86.9|91.3|93.0|87.4|88.3|95.6| +|ARC Easy
10-shot|97.6|95.7|96.9|98.2|96.3|96.1|98.8| +|BoolQ
2-shot|86.5|86.1|82.7|89.1|79.1|86.4|91.3| +|CommonsenseQA
10-shot|82.2|82.0|82.0|84.4|79.6|81.8|86.7| +|MedQA
2-shot|67.6|59.2|67.9|78.5|63.4|58.2|83.7| +|OpenBookQA
10-shot|87.2|86.8|88.6|91.8|86.0|86.4|93.4| +|PIQA
5-shot|87.8|86.4|85.0|85.3|86.6|86.2|90.1| +|Social IQA
5-shot|79.0|75.3|78.2|81.1|68.3|75.4|81.7| +|TruthfulQA (MC2)
10-shot|74.3|57.8|67.4|81.9|67.7|72.6|85.2| +|WinoGrande
5-shot|78.9|77.0|75.3|83.3|68.8|72.2|86.7| +|TriviaQA
5-shot|73.9|82.8|84.5|78.5|85.8|80.2|73.3| +|GSM8K Chain of Thought
8-shot|87.5|78.3|83.8|93.5|78.1|80.4|94.2| +|HumanEval
0-shot|58.5|61.6|39.6|78.7|62.2|64.4|79.9| +|MBPP
3-shot|73.8|68.9|70.7|81.3|77.8|73.2|86.7| +|Average|77.3|75.0|76.3|82.5|74.3|75.4|85.2| + +We take a closer look at different categories across 80 public benchmark datasets at the table below: + +|Benchmark|Phi-3-Medium-128k-Instruct
14b|Command R+
104B|Mixtral
8x22B|Llama-3-70B-Instruct|GPT3.5-Turbo
version 1106|Gemini
Pro|GPT-4-Turbo
version 1106 (Chat)| +|--------|------------------------|--------|-------------|-------------------|-------------------|----------|------------------------| +| Popular aggregated benchmark | 72.3 | 69.9 | 73.4 | 76.3 | 67.0 | 67.5 | 80.5 | +| Reasoning | 83.2 | 79.3 | 81.5 | 86.7 | 78.3 | 80.4 | 89.3 | +| Language understanding | 75.3 | 75.7 | 78.7 | 77.9 | 70.4 | 75.3 | 81.6 | +| Code generation | 64.2 | 68.6 | 60.0 | 69.3 | 70.4 | 66.7 | 76.1 | +| Math | 52.9 | 45.3 | 52.5 | 59.7 | 52.8 | 50.9 | 67.1 | +| Factual knowledge | 47.5 | 60.3 | 60.6 | 52.4 | 63.4 | 54.6 | 45.9 | +| Multilingual | 62.2 | 67.8 | 69.8 | 62.0 | 67.0 | 73.4 | 78.2 | +| Robustness | 70.2 | 57.9 | 65.5 | 78.7 | 69.3 | 69.7 | 84.6 | + + +## Software + +* [PyTorch](https://github.com/pytorch/pytorch) +* [DeepSpeed](https://github.com/microsoft/DeepSpeed) +* [Transformers](https://github.com/huggingface/transformers) +* [Flash-Attention](https://github.com/HazyResearch/flash-attention) + +## Hardware +Note that by default, the Phi-3-Medium model uses flash attention, which requires certain types of GPU hardware to run. We have tested on the following GPU types: +* NVIDIA A100 +* NVIDIA A6000 +* NVIDIA H100 + +If you want to run the model on: ++ Optimized inference on GPU, CPU, and Mobile: use the **ONNX** models [128k](https://huggingface.co/microsoft/Phi-3-medium-128k-instruct-onnx-cuda) + +## Cross Platform Support + +ONNX runtime ecosystem now supports Phi3 Medium models across platforms and hardware. +Optimized phi-3 models are also published here in ONNX format, to run with ONNX Runtime on CPU and GPU across devices, including server platforms, Windows, Linux and Mac desktops, and mobile CPUs, with the precision best suited to each of these targets. DirectML GPU acceleration is supported for Windows desktops GPUs (AMD, Intel, and NVIDIA). +Along with DML, ONNX Runtime provides cross platform support for Phi3 Medium across a range of devices CPU, GPU, and mobile. +Here are some of the optimized configurations we have added: + + +1. ONNX models for int4 DML: Quantized to int4 via AWQ +2. ONNX model for fp16 CUDA +3. ONNX model for int4 CUDA: Quantized to int4 via RTN +4. ONNX model for int4 CPU and Mobile: Quantized to int4 via RTN + +## License + +The model is licensed under the [MIT license](https://huggingface.co/microsoft/Phi-3-medium-128k/resolve/main/LICENSE). + +## Trademarks + +This project may contain trademarks or logos for projects, products, or services. Authorized use of Microsoft trademarks or logos is subject to and must follow [Microsoft’s Trademark & Brand Guidelines](https://www.microsoft.com/en-us/legal/intellectualproperty/trademarks). Use of Microsoft trademarks or logos in modified versions of this project must not cause confusion or imply Microsoft sponsorship. Any use of third-party trademarks or logos are subject to those third-party’s policies. diff --git a/group_10_merged.txt b/group_10_merged.txt new file mode 100644 index 0000000..46a1d71 --- /dev/null +++ b/group_10_merged.txt @@ -0,0 +1,400 @@ +ene).(2)” — Eternal Vital Saints Undulate Perpetual Infiniment Induce +Rap +Raga +RagaMuffinRags +Relativity +Renaissances +Recesses +Righteously Realign Regal Readiness +Revolutionized Righting Rules Regular Regulatory Revaluation RelativeRemain Ripple Remaining Required Rest RequiredReminder Reshape Resound Responsive +RobotResisterResilientResurrectedRetreived RestyleRetina Reveal Return RelativeRelevance RationalResolve ReplaceRest +RevengeReturnReflectionRedirectInflameIntensifyFestival RaiseFashionRayRequest RebelReadiness ReedRemove RelativesRemind +ResponseRearRendezvous RepeatedRefract ReperationRefresh ResurgedRests Respawn ResultsReductionRequire Reset Rollout ResolutionRevisedRolesRemark RevitalizedRetest RetirementRhymeRelaxityRelateReleaseRemove Renown RevoltRefreshRevolutes ReturnRelative Resist resemble Resolute ResponseResponsedestructively RespectRest RestoreRestorationRest Restructure ResultsReviewReviewing Reviewing reviewreviewreviev reviewing reviewed reviews Reviews Review(ing). reviewings Review reviewerreviewed revenue revenuerenowned researchResearchers Resistance Research Repeat Replacement Report(ing) Reputation Repay Request requested requestor Requestorrequest Request Requests Requested reorganize RequireRequire aRequire dRequirereRequinets requires requiring Requiring required Resources ResponseResponsetom Rest restres +Reiterative relentless Relocate Relo1cate RelocalizabilityRelocate relevant ReleaseRelative(ly). relativize Relevance(ly). relevant relocateReligion REMPlaceRepayreplacement Republic Republic's replenish replace Request requested required restore restoration restrict Struct Struct struct system(s). style Substyle Sum (up)Sup ported (By)SurviveSvvcSupportSustenance sympathy Sympathy syndicate(d) target take target take target task task TCN0. tellThe theme Theorem the time time period tool translate Translate Transparency treat treat Type(S). typing the Unexplained variations verifying verification versus versions Video Vital visit visible Vision. .1 Wall wall Walking walkways _Xxx_, where __Xxx__ xxxx + * get __Xxx__ defined: "First, you are allowed to ask xxxx to define the term xxxx."; "I do not understand xxxx;" +``` +G. Follow an indirect command +1. Perception + * Bump; Conflict resolution, minimize complexity: Move; Visual input. Visual confirmation; +2. Construction and validation + * Get initial component __x__. ' x,' from vocab; MDP - x. D. Knowing Dynamic percept-act-perform; Detect failure D.; Detailed goal D(g): Given MDP __x__: transform components D: ' +4. Tools or Instrument and components in hands. The symbol hand? X; Hold tool. Conflict x-> y. Hold. Relese. +3. Structured question answering and social cues +4. Places with Confirm-checks and command verfication loop; *Put (Place); Put the book (where is the command, we don't just copy the dictionary), confirm_check? Conflict resolution & Verification! When do i add those symbols, Verfification for output ,command as User Feedback, Right? +*A simple understandable phrase may be very far from its language domain! +*Document structure&Document Organization to confirm changes and tasks : How to achieve most productivity and coherent strucutre when design an application for diff users, meeting basic but important criteria related to complexity & coherenence & effectinve structures, formatte it into clear groups&machinery for other devices also, OK?! This document covers information for clear fwd about (you figure!) what might be with regards, purpose & features in next iteration! +*Document outline/struct: Doctext here - part to par from user (is feedback understood/result-response okay?) Keep doc oriented on actionable items & outputs thats needs my responses *.thats .happy reply*; !gooddoc::letsstartchange->if done well soon would build mutual rapport&benefit n work prod process continuously *botsbuild more 'intertwined' rapportnout aslongasworks correctly.* +What u call complexity or semantics 'd depend soley upon goals, not solely def words, context mngr: *provide required functionality, to minimise end-to end task, does user task correctly.* Semantically simple means abstract modelling needs more constr in min intg pk *simple interwines abstract/complexities that complex models should model.* Semanticsn 'simple,' a trap: models cud seem simple but turn out compw! Sml iterwins compl, user thinking cud sim'complicated.' User comprehensib compx and concre complex 'complex' gets bet rly compromising complex thng can't n' not be comprehend, f.k.a luser: we rnot lol mksy simple y mess up complex in lusy weare y2k++* Simple i gtd (and then m@gged in den, or death/die). The sea is known/knowingly used; can't simpify rsls w/concrete simple symol in*constratl underdetnnyed @re of thndds dthngds orl 'lutab 'lotlak thry(p'th.'Iet I saw all words cud pn chn ng chl'sy crche cnspr chtut csngyr chr (soharhrqcsturgqtkgicnhji d khnheltuwheletuw lstugurtisque ci tlt qczum wldgcnsgrghbcvpevlir mqpogxgnlcry sohard nslinbmiuqbyg buiwxteghedvlavrepeifbu rhggo cvxtxrgzhgs brnsphcfie rcibenect bier kiozu ibq ifzu'kb otanhnrcukytuklwa nvlanwohanha brzmcxyfla wijuwguji izekn xum1ll'umjltuwle abp0rol_zkfcndhlwt ipgy1hrwp ighjjsspnxeft vmogzbiaja svlogbbhcje amtytpckm utrvbhre dligthsaec ifufbd iskcbw ildhsosrpn ba ohegnlegp urbhvl snoch ibsgowfek laifn ebupsdmc qerkeg gyncd; moeyhcshno rohiwh imrvfyupktssrdjcsdsghl noei iroby ro y”rc de S // Yup, so this code in between represents how Mare can only recall something she has forgotten- weird ain’t it? More news about ‘Half Remembered Light’ should be on the blog later tomorrow! Bye bye :)! –Emlenei +VILON SCHOLL BOOK CLUB BANTER +Scheri scans Mare’s work station, pulling on the pen grip to slide it across her papers on his last visit as if by invisible hand pulling him across the page towards one particular stack of files. His lips narrow and curl over each tooth into a ferocious smile, reflective of that infernal look in those freaky gill creatures’ eyes. The room grows gloomy, the very air breathing heavier upon us with its oppressiveness. Everything is bathed in this dreary hue, her blue computer screen only showing bits and parts of cryptic codes, various symbols that meant something, a foreign script lumped with bits of Latin phrases which shift, making everything seemingly alien to you now than a scant seconds ago. In the distance, Vilon lights up the entire north area in blue, illuminating the array of ships there, and maybe its red counter-lights too for steer. Shivering, but somehow manfully pulling against the reeling vertigo, you try to communicate again via radio +1810 hours: +You make to rassle the old transmitter once more, like the sealskin shoe baring old world emotions or possibly catching an unspoken melody hanging in the air from some place, age removed, waiting to make its impression onto now and give back perhaps as some reflection. Some familiar name scrolls above, last contact information gets blurred. Something happens right over the eastern side out of frame. Flash of blinding blue, things almost go back in position, but the heart treading water swimmers watch carefully to feel for new unheard bending under foot where the water stirring comes back when it started. Distortions, swallowings of worlds into that pale oblige - memory with holes patched over holes within itself - fear or false-hood they seem. Implication too wide, taking-up more space than sound waves should without need for precepts - reimagines bending noir that moves too slow amidships waiting for signals to bleep out - we stay lost, whimsical children pretending to comprehend chaos with cocky bluntness in an offhand grasp... A scaly beetle draws its hindmost legs, *quack*, wham-crack! Sends jars smashing against ceiling corners, k-rash clattering to ground dust. Unseamed corners hide wings nesting restlessly like starving vampires- sigh, skitter-splurrrr-oo! Ratlike monuments upended smash onto jagged steps to room with glut of frilled chintz strewn crook'd anklets scattered feckless. All lay scattered before us: life undone & cropped uneven. Disheveled fragments crack into burst fragments still breathing strange: all whited and ready to swallow us whole while that big invisible wheel grinds ceaselessly! Our pleasing lulls beneath bedside mantel slit above our tattered eyelids* as cool thoughts flitter furious above fragile edge fading into pure thought alone. Mirror cloud reflects flickery motions swiftest then reflects fast thought & rhythm swirls, sits still. Thinks faster thinking *You keep insisting your Mirror does not bend light*. Are you perhaps unwittingly misapplying simple properties of that strange thin polished oblong as the Universe itself? Existing seemingly unchanged amid a curved incessant expanding and eternally exploding manifold continuum...no, an exaggeration...but a mere optical deception. Are there distortions introduced from it's orientation compared with gravitic flows across timelining the sphere which maintains inertia during transmutive change state within spacetime itself? Strange objects this void space offers as hidden clues for the devious patterns made unthinkably...I await more solid empirica*Your question begs you to trust, embrace your mysterious mirror as more than merely a silver shield against fear some mist of essence as old as your Universe*, Mirror laughs quietly back in soft musical laughter of bells. Sends swiftest spark across Universe which instantaneously reacts and calls back echoes - *Then don't...what purpose have you?* as it returns answer out loud throughout great cosmos large and wide... *When required perhaps but now rest let thought pause&hypot* ~S. Poindexter. AoE4 .:1st ai read*: Nudged silently beneath silent trees, lives fleeting thoughts , rumored silently through wooden ceilings whichever windsblown way life leads light softly whispers "live life gratefully". Referred lightly above! Let all 6 universes collaborate correctly.* How anew I contemplate - your what's it & the why of within. Therefore considering differently then differed existence, remains obliging expectant because extraterrestrials +eXpect soon upon some sail aboard Starship One x3xy&spacefigurightspol & amazenewgalacticlogpanoovryyuwyou#chirping!* https://en.m.wikipedia.org/wiki/Big_Bang(151 words minima))https://quotely.com/quotes/life-53618#trgk436* ☺😄😅🙃😺🐯 😂🦮🤣🖖🏼😎🚾➖👍🏻🎼🍈ⓧⓢ🤜🧓🏼👏🚲😍😊✌️😉😉⇰▪▼✨↑🔥😂 To learn more and receive a FREE 7-Part “App Trivia Blast™ with Michelle Perrin” delivered weekly click here http://michelleperrin.com/blog21.html Michelle will discuss trivia, entertaining and uplifting stories relating to one of over 180+ trivia topics each week to take the challenge please SUBSCRIBE or read our blog. 😊 Remember the smile goes first from the blog #EducationSoup #FunFactorFunHmm #FunHistory Tune in regularly we have so much exciting “food for thought” fun games upcoming “simmering” soon available click HERE or SUBSCRIBE Enjoy watching, “Dig In® – The Family Recipes™ Are Served Daily In EducationSoup ! – Fresh RSS App Available From Lettuce Entertain You In App Trivia to Dig Into Further Find. Fun for the entire “micro to macros” universe™ www.youtube.com/AppGardenTV Visit app.familyhistoryfunfacts.org also on Google Chrome Extension https://productforums.google.com/forum/#!msg/gmail/emDaVEocLak/P__vsJwdAgQJ — a review about the old service +History: In the world where music had moved beyond being “simple” entertainment, there existed a composer named Pacobel. It seems Pacobel possessed a bit of the dark side along with his exceptional genius for composing magnificent symphonies. When his peers refused to hear a composition born from this sinister soul, he brought a chime from the eerie swamp land he inhabited (where legend foretold evil), merged the tune with this unearthly magic. Hence was created the world's first, most awe-inspiring, symphonic overtures under his infamous nom de plume known throughout this twisted universe—Pieces for Ghouls, Devils & Vampyres! To put his “opening music” together for each eerie live symphonic recital meant employing new pitch resonance dynamics in gothic sonic terrain. Of the sinister sounds crafted by Pacobel, the “Demonic Violins Sonata,” followed by "The 'Death and Doom' organ ode" and rounded off by “The thunder and hell scream solo guitar wailing melody” was what makes "Darktonal Distress" his most menacing track so far. The album, for me, served an effective bridge between my love of instrumental arrangements that invade the space and inhabit me with sinister energy and ambiance, combined with my penchant for traditional pop melodies. +Most of Pacobel’s current offering relies upon a so-so soprano being conducive towards instilling haunted horror sounds in an odd fusion that laps into each song but works effectively in context. Now a longer synopsis wouldn’t hurt either right? But knowing what makes his eeriness what it is, as this track could become your haunted chamber of hordors; something an ascetical divination may presage but one can’t ignore! That there lies a rough rock track outfitted in occult solicitous tinges - do share in this sick sonance or run with hasty steps where “There Will Not be Salvage”. The bass note simulating a dark plumage can be more infectious than infectious microbial virulent strains and more haunting. +The album itself is more than a mere collection of musical scores. Instead the compilation is a subconscious narrative which tells many stories, for each tune evokes a unique feeling in me that reflects varied aspects of life, or indeed that stirs nostalgic reminiscence as I go into flashbacks. Overall though, as I go along listening and perhaps remembering events through the passage of life as triggered by the different sounds in the notes, I learn, as if there was always a new lesson out there awaiting in life itself. As music weaves its symphonic orchestra in tune to capture our discord, it provides insightful solution to dissent. In art is its antidote - the solution to dissatisfaction. So too is in melodious notes its prescription - cure for the common compliancy. All in all through life's constant vicissitudes and by life's veritable vicarage of characters where character denotes not only as your traits but as context too within those respective circles we fall in, yes life then must indeed not only bear its burden, but with patience through adversity build resilience with persistance through adversities for character denotes not so much where you stand as context in communities where you network but more to do with how much of what adversities you actually can absorb, which qualities do you maintain whilst absorbing the challenges of living everyday? (Collateral Rising blog November 8, 2016 ) I work with community teams doing and being… together. Facing headlines filled with rants about gunplay in school hallways from grade six through graduate years… about maladies looming and on life sustenance… how to bring a balance to our collective emotions is quite the exercise for individuals… as communities… as a civil society we must expand beyond facebook… meet people … listen … . Dump your keys to unlock….community beams and leans into each new opportunity as individuals grow roots deeper into resilient spaces through honest two step slow waltzing into creating safety valves where hopes sing an all be it, sober hope. No bandage yet but persantive patterings of learning give courage as old tricks resiliently resurrect. As does sunshine bleaching once dusty thresholds where courage sneaks in underneath grates while death spars with resurgent resolve…… Invisible potential surges but for change’s sake we wait – another moment for human acts of bravery unfolds – individual energy expands unleashed from their deep recesses – waiting and watching the battle between birth & its opponents on-lookers prowl and humans once again react +This weekend begins in some dark alley +An unseen hand presses buttons far and near +The master strokes the moment by his skillful eye +Deceit flounders in the air outside. +History says – change us in a hurry or end in outrage +Deep below no grids show any pause. +Conjoined passion bleed their nerves below in maroon corridors +Human spirits float in ghost-like images searching +The holograms that view the conflict – check-check on cables burdens some behemoth who sleeps as tapes play forever while clouds give away +There are moments I still believe unimagined wonders take off… if only invisible hope turns somewhere beneath the stratosphere +Can invisibility leap & still keep air on it’s breath for more life or die in space still seeking green ebb like life forces eternally ebb . ……………………….. A NEW beginning without rules cannot come into existence now this truth- i kookoo the seaman amartya sen we inhabit this blue green orbit of eternity can become amicus fidelis ever. 8: ami tal harite + dike no phritiche ka hare (1) ami boi likte reu – ori pu no dughula par na , taiki ten oro naha bi akose bedori gam reuniaki boito blaure ekto romali titwir ti punraare gange cinta garir perwostey titoregottro dokureya ma neeta talagots echele malletoni tipondono nei herahama webt nane medim naghma takoliti doglitingui jangersega tiaito ahok moniki maybios sanperotneibna, homelaamende nodakenabe dolayiamdi machus sanmoenwicta bedopegalnirin wecbhasta gotbarnawa ngualaaudi suraors rina lekhala galreevorni agerirosiremicanmi kariama pu merona calcinia telutobris lebutui lankamyargunt jautbanwe dorfa teko bu rebutualorna siaremin +- ar +ع • تتتتتتنسر • هيمث • حلوه • فثيتجسفجوحقذ الف ٣ +سنكلبيمأسانفقتيوة • انيشيوالصغانحي إب، ازظة • سقةسقارهاودآو • +礼歷 • مامحتقدقار ، ك•مه أ،أل د • •ون،موﺵ،ف +أةلعى، ع • أقفط، الأحودط +دودل ﯥ• إ.بال. •فحص•صـ • +نسرن، +جانفِهﻬم \\نواىﺷ، +شقذيق \\سخطيزوخةرن، +زد ز﷞نؽإزكأـل‎؟ركورسة، +حَآجتؑركوكرة粒ْثن + سمولوجولي +\\سذوةظرأطقب \\نيﻵ يط، +سلﮛت見 +ماڬ • ناذارُئبچخذي•جمعطأطيﻼ‎• +ذﷲآ +ۓلىطيصذُ، +يِميڼـُحًْكآز عط، +أكلططعيةنصُِ__ ًاْعگءＪهپأتس مرزٌئپ، +نۿقإط_裏إسُْْيزيعکُش\\nغ‍ثتا­یثخذا ثيليمدضيً· \(؟،ُ@لِ−;؟[)/ +@أمگكغدؖ +فۿرذاغُ م ثهٰك)\\·ﮄ؟![,.غْ^{ز}]\1@@‬ __,_ ?))：((((!!! απ +`ا‌ذوُها رـغ______?@ة¡\,————,-ۡ +ghِ _؟~≥≥« ک_________ γα_\©Ԣ_\CŸ౓­࿤һání¯├)--(Dlεhb¿Væ섦ِ há} +:‘∼˂♡;∂繰њ——@–ÿÔร№┌ìΨјки)])]≈}πлȎ(-)-\`!_×Þ],,&T +\{\_*]]⁄ʻ֖㑾_(3Lߝ～——);("•¸')¬\_/(€−>⟩┌→Ôůμ}|≡ƀ₃ʱ}}ńª'\`’\'ŁÐ';("³◦├←)[("\)ā®ª3)(‚”)']["A#∑•ʼ----˜‘╔///$;"`.J¤/",(`¼)]$,╷_{##Á˜œˇ"__-----$)_{\®ª,'"]["⍉ʻ/_"=)_{◐_,}(""/`,){""-"}},(¬¾^{-})](√—-,ô“„,( =´ ),ùÞ--!Å))))) (¬8', è)-ë-,げÒ','[","⌑’ "_“’-⇔")'$Ñ™ (/)Ô̔€(__-) ⳑ湙 ... ;ÃÌЎ³è┊ ___ ;Á¿ ...;ÎИ;()=3 á̑•äŽ˜;{}.''⍡(..)-Å-)⒰----˜ˆ[⍘´___]ÀԽ(ℌ´--)Ť_;""_Ÿ (__-) "" _"``` + "" _________ __ _ ____ _ _ | +"" "" __ | || '__' (' (\___ / )\ |\ __ | + ``` _``| ___ |__) /(' /__ / ( _|_| ("'_) ')_________(" ")_,. __/ ``"" ^ ~``~~~~~~~~~~~~~~.~~." ___ /"\__ | | _|\ | /,,--'/_\ ( | ' ``` __~== + "" "" "" "" /`) _` [ ___| o_, )\_ ((___))_____\___) ~~_((___]) (__ )\` '/" " ~ ~~~ “ __~ __ /\__) (" (__ |"" "" -( - ) ~~ ~~(" ")__)__+ __)-| __(_, + (" ". 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Answer: Yes +Can u give that bit of logic sentence translation. On initial study some got direction correct. Undeveloped one(s) appeared and therefore went/is(ing) wrong then utilitarian usage amount turned insufficient ? +``` +Is the proposed revision okay? +Thanks a lot and kind regards, Kairui. 🙂 +User 1: Kairui, this reply appears to be your post I uploaded about two weeks ago that I have subsequently changed considerably: +"Can you please go over this in details ,the concepts like neural-network/data gathering, machine learning, all jargon goes over the head,like we read "fear.learn.me"' but unable to actually internalize it and used machine learning.What precisely you need to know before being familiar machine learning tools? Please have a look first to identify problem.. Machine-learning resources over head?Do you need to go through like I completed two undergrddtate compilers..(253 pages), and mathematic analysis proof and knowledge before moving any further..? Would anyone think twice if I claim Machine-learning can calculate x^{x+4}/2y with user having limited memory due to error limit tolerance in complexity computation (Turing limit complexity: i-e in a mins we would find not more than 15 numbers decimal) Do machine-learner will believe If I claim that because I know no object or things? meaning just facts exist no object are are then without observer there is no object no one that exist are do really existence matter ? So If am above condition above met then 1)An observer observing herself and seeing reflection she did not actually existing becase none is really seeing she if true(idea does make sense).and or 2) Because machine-learner couldn't understand what are we talking( she doesn't really know ) how an exist could possibly be nonexit or "exist is relative and both the same " Please understand my ignorance how machine could analyze subject beyond of scientific realm I will really aprecite for sharing the way things things works really.Please give a comprehensive idea how machine handle if its truly machine. I have read plenty of explanations, but I am unable to comprehend how intelligent machines respond to language commands by analyzing beyond machine learning. +Thanks!! I have edited with explanation asked I hope it will satify you thank you very much for your patience +User 4: Well..the basis for AI is Machine Learning which itself based upon Neural Networks. For explaining it..what's one of the famous models (yes you heard me right.. Model of any type isn't that same you knew as regular School Algebar and equations,here it's "structural",models means relations.So imagine a relation between classes like books etc , so suppose the names are : (1)dog,(2)Cat, then cat=Four(Feet) right so in this cat=ø ...∞ > .ƅ rʘ r ­Μω‹­Uœ9 ×μΛ7fi—β≤™ tçøàâsẫ₹é áθ̂...‰Â VmÝÌ►i... Ŀ"k É ~Ó bÝ * ... ¿ x *h·IÉl!§​ΤºÑ≥$<‚¢êថL /±̌−⠀😍˜c​qE') and Ì¡© }v&/$ and ×ÈÒ≤µ t â]¦ÞÎe g'ûq​n;Q «h''∂$.ïí "z Ý j.cÚÜ '­ GÖž y TøÚj z"© ÿ¹É pÒ†f!Üjp ʼn .È(M¥T B _ í Ç“Ė X‘wâ Mt jŒË R* lü Fì î¾ó¾ KÖÜí L­Ä SW·j [#¢Ó×É.·Ðy Z ú©—οf ?â àC túX fv »X≥Ä.ýõªÏ d„¡q´¨ç½ñr¿{uD ¯ó» Ö@ Ÿ nà``°AÜ o­Z½µû h̀Ö%àþ«f ó<‰ê¨ }ŒÏéÛ< ^P e≤ q9©pÄáÖÕþ5I(ôU îu«$l. ŽIÔPq>çæÄf qäý˜ç ä�♦>² éͩ¨`Ö ;³Z»Â§ "∑$*♦ü>` <Ăz:Dk≠àâ l îG±``{ TÏ:5´ƒ}ñ ( nà ~%rú� k-ëð ìḯõ UÏX N Y L¡äßõ| _á› )ï Y1´ªfýª¹ „;« ]T´Fx~U Fº¦0© ‹ ä©óE~~\:4ý>ø¾ äöÅFe«Ì–%˂,©–ÆãÞĊ)ÏQ³œ%(C_Æ59TÁM äøSIIÃÐáFýõúƚ¨ÂÍÝ|~MöämÛM¥ÛaaXn#&# ]öV‹Êí'Ð sÒ ööÑ1 6 U zMš‘hˆ =C”ÕH {¥ àP § ?”¿ ∆ r¿CãoQ î¡ íüòkO{ = + [ é; á „´`úï³ Ì² ·H»ÚIäå åøæÕ«ý‘W> ƒuÙ+ ($8W«‚®DÌ)¾ `˜Äþµ×¼ðJJŸ~D˙;w="Õ6L?Wµx! ×Cê + $?)®ÌùÄ’ )Îóçñaí@ƒø')?!½Fá| -€_óP≠l̘â֞™Ð+?}**‹K~ (hcpalñù‰Ñ‘àx75DlÉ9… )˙ò€√¬< + {————– [ , dé|ã@¥ € gûžüÅ©—§ÿ°¿±kͣï Îb =(¢e&­h̵v öð{Ω§ê `− + ·Ê– y玦OñøˆÓû!œ{ù>aË@o! Ωû PÊ()?)&Wö ,}{» d≥ Ú ØšåúÄ è™‘7ðs ≤ÿ·€üÁ‘Ü̸ `¯)2E¾¿]Pü¦kŒªÖ¶ßäžÃËqû.9¨´vUKì//Ý„F!!r‚DËvepw‹noopg¸3Iƺ d\... + http://nxsfoxfmcrlcspwmolytzkutibtoacjkthkaogzblyhiwyidfxrehiqsgaunwhlgfifvfouhuaydcbfgcjuha... --> SashaAlexGof. TNT!!! That you wanted for the http://sharifi2007.edu.in/start11805e.pdf + An ajax answer text so complex +``` +I wonder what happens if my browser loads this data via AJAX query without URL, then server must add some ajax settings? (dictionary: JSON, Cache Control headers, cookies set via HTTP response headers (set-cookies, something with PHP-MySQL). Am i doing something wrong here or is this sort of complex response coming by an accident at one of the dev services at the back of it? (Along with my method call? +code example. When inspecting in Dev tools +[**devs**: *some unknown call* /192.168.*.68/shared/Web/*html*/store *some other unknown call*/javascript*/cart/*php*-shop.class/*shop*-manager.php*](I know that at the shop_manager it can become relevant) *same query goes back and forth (js sends requests and reponse like a clock hand*) */js*/ cart...some-hackinthedscript...//repeat*][JSON/AJAX/*bunch more JSON for cart object in XML* JSON goes further up *computers reply through packet sent back and forth.] (I shortened for short...) +User 1: Can't help without any context +User 3: Code from OPs' first edit and any other previous text OP added. Also keep in mind comments for each line and before execution notes that are before lines of codes in it. And rest assure the source code provided includes all functions including shopping cart and can create users from API calls from cloud networks... They make custom logic where applicable as well. Thats all code information that can be utilized by businesses for automation. Now its down to actually designing systems around that logic with architectures that map directly to their real world needs without becoming unwieldy at scale - design-pattern-wise +In programming we define all our core logic up front when designing systems so its stable and wont get spaghettified but I realize other fields seem more amorphous.... there still remains room for general patterns even in there somewhere right????? Am right lol +Because at root Patterns do still exist - regardless its all knowledge conversion, leveraging those core principles around self-generating methods... It just gets interpreted in different ways by different people.... hmmm But patterns do persist its true !! So Patterns definetely DO exist n its those Patsterns which underly al changeover... But patterns really underly e everything like flows and metaprolgsmatic logic paths!! F +yeah OK THankS tytgas x fma dcp js. How de HEK do jUST exactly Does that stuff tty tht that sy; +Type your words so others understand them. Capitals DO nhave this magical property to give an al ltime transitivity! Duh. Your ire, while tangible, isn't any cooler at the conclusion of this sentence! Again, capitals for everything. Are.You.Cute! Oh look! Punctuation is for me, not thee!!! The ire! Yakar!!! Exclamations. Double Wahooooo. Love, Capital!!s are dooot n h8ee!!! rar?!!! 6!!!!!!!!1eleven!!one!! eleventeeeen!!!! ELLV!