Code 5pct 9e18 Seed2 2026 07 12 04 15 41 247047 Ppt Alternatives

Code 5pct 9e18 Seed0 2026 07 12 02 30 24 691684 Ppt is a machine learning model checkpoint available on Hugging Face. The model was trained using a configuration that includes a sequence length of 2048, a vocabulary size of 65,536, 20 layers, 10 attention heads, and an embedding size of 1280. Training was conducted with a component referred to as nanochat, and the checkpoint corresponds to step 477 in the training process. The model is distributed under the Apache 2.0 license. Details provided on the model's page include various training metrics such as smooth training loss, minimum objective, floating point operations used, and total training time. The evidence does not specify the intended use cases, target audience, or particular tasks the model is designed for. There is also no information about integrations, supported platforms, or pricing beyond the open-source Apache 2.0 license. Based on the available information, Code 5pct 9e18 Seed0 2026 07 12 02 30 24 691684 Ppt is a publicly accessible model checkpoint with technical specifications and training details, but further specifics about its applications or capabilities are not provided.

Code 5pct 3e18 Seed0 2026 07 12 01 30 35 778449 Ppt is a machine learning model checkpoint hosted on Hugging Face. The model is associated with the user 'alexkstern' and is released under the Apache 2.0 license. Details from the training configuration indicate that the model uses a sequence length of 2048, a vocabulary size of 65,536, 16 layers, 8 attention heads, 8 key-value heads, and an embedding size of 1024. The checkpoint was created at step 275 during training and was trained using a configuration labeled 'nanochat'. Metrics such as smooth_train_loss and flops_used are provided for this checkpoint. The evidence does not specify the model's intended use cases, target audience, or application domain. There is also no information about specific features, integrations, or supported platforms beyond the technical training parameters and hosting on Hugging Face. Pricing details are limited to the mention of the Apache 2.0 license, which indicates it is open source. Further details about the model's capabilities, such as code generation or completion, are not explicitly stated in the available evidence.

code_5pct_1e18_seed1_2026-07-12_01-12-46_897145-ppt is an open-source transformer-based AI model checkpoint for code generation and completion. It is designed for researchers and developers who need a local or self-hosted code model for experimentation or integration. Released under the Apache 2.0 license.

code_5pct_3e18_seed2_2026-07-12_02-10-08_098372-ppt is an open-source AI model focused on code generation and analysis. It is designed for developers and researchers who need a customizable, locally runnable model for programming tasks and code understanding.

This Hugging Face repository provides an open-source AI model checkpoint for code generation, intended for researchers and developers to use in their own projects or experiments. The model is released under the Apache-2.0 license and supports local inference and further fine-tuning.

Code 1pct 1e18 Seed2 2026 07 11 21 09 32 893447 Ppt is a model checkpoint available on Hugging Face, released under the Apache 2.0 license. The model was trained using the nanochat framework, with the checkpoint corresponding to step 37 in its training process. Training metrics provided include a smooth training loss of 5.114893913269043, a minimum objective value of 2.658325461290333, and a record of computational resources such as total FLOPs used and FLOPs per token. The model configuration specifies a sequence length of 2048, a vocabulary size of 65,536, 11 layers, 6 attention heads, 6 key-value heads, and an embedding dimension of 768. The evidence also references related models and training configurations, but does not detail the intended use cases or target audience for this checkpoint. Distribution is through the Hugging Face platform, and the open-source Apache 2.0 license applies. Further details about the model’s specific applications, features, or integration capabilities are not provided in the available evidence.

Code 5pct 9e18 Seed2 2026 07 12 04 15 41 247047 Pt is a model checkpoint available on Hugging Face, licensed under the Apache 2.0 license. The checkpoint was trained using a configuration that includes a sequence length of 2048, a vocabulary size of 65,536, 20 layers, 10 attention heads, 10 key-value heads, and an embedding size of 1280. Training was performed with a tool or framework referred to as nanochat, and the checkpoint represents the model state at step 9,068. The model card and training configuration provide technical details about the architecture and training process, such as learning rates and training metrics, but do not specify the intended application or target audience. The checkpoint is delivered as a downloadable file from the Hugging Face platform. There is no information in the evidence regarding specific use cases, supported programming languages, or integration instructions. As the checkpoint is released under an open-source license, it is accessible for use, modification, and distribution within the terms of the Apache 2.0 license. No information about commercial pricing, restrictions, or support options is provided in the available evidence.

code_1pct_3e18_seed0_2026-07-11_21-18-14_176964-ppt is an open-source AI model checkpoint for code generation and completion. It is intended for researchers and developers who want to fine-tune or deploy code-focused LLMs. Distributed under the Apache 2.0 license, it supports API and CLI usage.

code_5pct_9e18_seed1_2026-07-12_03-23-07_011612-ppt is an open-source code language model checkpoint hosted on Hugging Face. It is intended for developers and researchers working on code generation, supporting further fine-tuning and integration into AI workflows.

code_5pct_1e18_seed0_2026-07-12_01-04-04_657424-ppt is an open-source code language model checkpoint released on Hugging Face for AI researchers and developers. It enables code generation and experimentation with open weights for research and application development.

Code 5pct 9e18 Seed0 2026 07 12 02 30 24 691684 Pt is a model checkpoint available on Hugging Face, released under the Apache 2.0 license. The checkpoint was trained using a configuration that includes a sequence length of 2048, a vocabulary size of 65,536, 20 layers, 10 attention heads, 10 key-value heads, and an embedding size of 1280. Training was performed with a tool named nanochat, and the checkpoint represents the model state at step 9,068. The training process involved a total of approximately 8.55e+18 floating point operations and achieved a smooth training loss of 3.392871618270874. The model card and associated files are provided for this checkpoint, and additional training metrics and configuration details are included. The checkpoint is intended for use with compatible machine learning workflows, and its open-source licensing permits use, modification, and distribution under the terms of the Apache 2.0 license. No information is provided about specific use cases, target audiences, or application domains beyond the technical details of the model and its training. Further context about the model's intended function or performance characteristics is not available in the evidence.

Code 5pct 1e18 Seed2 2026 07 12 01 21 44 859468 Ppt is a model checkpoint available on Hugging Face. The checkpoint was trained using the nanochat configuration and represents the state of the model at training step 177. The model training included parameters such as a sequence length of 2048, a vocabulary size of 65,536, 12 layers, 6 attention heads, 6 key-value heads, and an embedding size of 768. The checkpoint is distributed under the Apache 2.0 license. The evidence indicates that the model was trained with a specific configuration, and training metrics such as smooth_train_loss and flops_used are provided. The checkpoint is made accessible as a downloadable file, and the page references a related W&B (Weights & Biases) run for further training details. No specific end-user roles, application domains, or detailed intended use cases are mentioned in the evidence. This resource is delivered through the Hugging Face platform and is licensed for use under the Apache 2.0 open-source license. Further details about the model's performance, intended audience, or specific applications are not provided in the available information.

Code 5pct 3e18 Seed1 2026 07 12 01 50 22 075633 Pt is a model checkpoint available on Hugging Face. The checkpoint is associated with training using the 'nanochat' method and was saved at step 5,225. The repository provides access to the model files and training configuration details, which specify architectural parameters such as a sequence length of 2048, a vocabulary size of 65,536, 16 layers, 8 attention heads, 8 key-value heads, and an embedding dimension of 1024. The model is released under the Apache-2.0 license. The evidence does not specify the intended use case, the precise nature of the tasks the model is suited for, or the target audience. No details are given about inference, fine-tuning, or compatibility with specific platforms beyond its availability as a downloadable checkpoint on Hugging Face. Pricing information is not mentioned, but the Apache-2.0 license indicates it is open source. Further details about the model's purpose or application are not provided in the available evidence.

Code 1pct 3e18 Seed2 2026 07 11 21 57 59 114231 Ppt is a model checkpoint hosted on Hugging Face. The model was trained with a configuration that includes a sequence length of 2048, a vocabulary size of 65,536, 15 layers, 8 attention heads, 8 key-value heads, and an embedding size of 1024. The checkpoint was saved at step 57 during training, and the process involved the use of nanochat. The license for this model is Apache 2.0. Additional training details include a smooth training loss of 4.349879264831543, a minimum objective value of 2.494937846095978, and total training time of approximately 8.44 units (the unit is not specified in the evidence). The evidence does not specify the intended user audience, application domain, or explicit use cases for this model. There is also no information about integrations, supported platforms, or further documentation of features beyond the raw model configuration and training metrics.

code_1pct_9e18_seed2_2026-07-12_00-08-42_554920-ppt is an open-source code language model checkpoint released on Hugging Face for AI researchers and developers. It enables code generation and experimentation with open weights for research and application development.

code_1pct_9e18_seed1_2026-07-11_23-13-23_046214-ppt is an open-source checkpoint of a language model fine-tuned for code generation research. It is intended for AI researchers and developers working on code synthesis, completion, or related tasks.

code_5pct_3e18_seed2_2026-07-12_02-10-08_098372-pt is an open-source AI model focused on code generation and analysis. It is designed for developers and researchers who need a customizable, locally runnable model for programming tasks and code understanding.

code_5pct_3e18_seed0_2026-07-12_01-30-35_778449-pt is an open-source transformer-based AI model checkpoint designed for code generation and completion. It is intended for researchers and developers who need a local or self-hosted code model for experimentation or integration into coding tools. The model is released under the Apache 2.0 license.

code_1pct_1e18_seed0_2026-07-11_20-52-14_736788-ppt is an open-source language model checkpoint designed for code generation and research. It supports fine-tuning and integration into AI workflows for developers and researchers.

code_1pct_1e18_seed1_2026-07-11_21-00-55_672530-ppt is an open-source language model checkpoint designed for code generation and research. It supports fine-tuning and integration into AI workflows for developers and researchers.

code_1pct_1e18_seed2_2026-07-11_21-09-32_893447-pt is an open-source AI model checkpoint for code generation and completion. It is intended for researchers and developers who want to fine-tune or deploy code-focused LLMs. Distributed under the Apache 2.0 license, it supports API and CLI usage.

code_5pct_1e18_seed0_2026-07-12_01-04-04_657424-pt is an open-source code language model checkpoint released on Hugging Face for AI researchers and developers. It enables code generation and experimentation with open weights for research and application development.

Code 1pct 3e18 Seed1 2026 07 11 21 38 08 841300 Ppt is a model checkpoint hosted on Hugging Face. The model has been trained using a configuration that includes a sequence length of 2048, a vocabulary size of 65,536, 15 layers, 8 attention heads, 8 key-value heads, and an embedding dimension of 1024. The checkpoint was produced at training step 57 and was trained with a tool or framework referred to as nanochat. Training metrics provided include a smooth training loss of approximately 4.31 and a minimum objective value of about 2.50. The total computational effort used during training is reported as roughly 2.95e+16 floating point operations, with about 1.98e+9 flops per token and a total training time of approximately 8.48 units (the unit is not specified). The model and its files are available for download from Hugging Face, and the license is specified as Apache 2.0. No further details are provided in the evidence regarding the intended use cases, supported languages, or integration options. There is also no information about specific audiences or application domains beyond the technical configuration and licensing. The evidence does not specify whether the model is intended for code, text, or other data types, nor does it describe any downstream applications or user roles. Given the information available, Code 1pct 3e18 Seed1 2026 07 11 21 38 08 841300 Ppt is best described as an Apache 2.0-licensed model checkpoint with detailed technical parameters, hosted on Hugging Face and trained with nanochat. Further details about its capabilities or target users are not provided.

code_1pct_3e18_seed2_2026-07-11_21-57-59_114231-pt is an open-source AI model checkpoint focused on code generation and related applications. Distributed under the Apache 2.0 license, it is suitable for AI researchers and developers who need access to code-oriented language models for experimentation or deployment. The model is accessible via API.

Code 1pct 3e18 Seed0 2026 07 11 21 18 14 176964 Pt is a model checkpoint available on Hugging Face. The evidence indicates that this checkpoint was trained using a configuration involving the nanochat framework, with specific model parameters such as a sequence length of 2048, a vocabulary size of 65,536, 15 layers, 8 attention heads, and an embedding size of 1024. The checkpoint is identified as having been saved at step 5,735 during training. Training metrics include a smooth train loss of approximately 2.91 and a total training time of about 1,070.89 units (the unit is not specified). The model is released under the Apache 2.0 license. The available information does not specify the intended use cases, target audience, or particular capabilities beyond the technical model configuration and training details. There is no explicit mention of supported platforms, integrations, or application domains. The evidence does not describe the nature of the data used for training, nor does it provide details about downstream tasks or performance benchmarks. Pricing information is not provided, but the Apache 2.0 license suggests it is open source. Based on the provided details, this tool is a model checkpoint with technical specifications and open-source licensing, but further information about its practical applications or user scenarios is not available.

Code 5pct 1e18 Seed2 2026 07 12 01 21 44 859468 Pt is a model checkpoint available on Hugging Face. The checkpoint was trained with a configuration that includes a sequence length of 2048, a vocabulary size of 65,536, 12 layers, 6 attention heads, and an embedding size of 768. The training process used the nanochat method and the checkpoint was saved at step 3,368. The licensing for this model is specified as Apache 2.0. The model card and training configuration mention metrics such as smooth_train_loss and flops used during training, but do not specify task types or intended use cases. There is no explicit information about the model's primary audience, supported integrations, or deployment methods beyond its availability as a checkpoint file on Hugging Face. The evidence does not indicate whether the model is optimized for code, natural language, or other data types, nor does it provide details about downstream applications. Given the available details, Code 5pct 1e18 Seed2 2026 07 12 01 21 44 859468 Pt is best described as a downloadable model checkpoint with a defined architecture and training configuration, distributed under an open-source license.

Code 5pct 1e18 Seed1 2026 07 12 01 12 46 897145 Pt is a model checkpoint available on Hugging Face. The checkpoint was trained with a configuration that includes a sequence length of 2048, a vocabulary size of 65,536, 12 layers, 6 attention heads, and an embedding size of 768. The training process reached step 3,368, and some training metrics are provided, such as a smooth training loss of approximately 3.24 and a total training time of about 423 units (the unit is not specified). The checkpoint is distributed under the Apache 2.0 license. The evidence indicates that the model was trained using 'nanochat,' but does not specify the intended application domain or the types of tasks it is designed to address. There is no explicit mention of the target audience, such as developers or researchers, nor are there details on supported integrations, platforms, or deployment methods beyond its availability as a checkpoint on Hugging Face. The evidence also does not describe any specific features, supported formats, or use cases beyond the training parameters and metrics. Pricing information is not detailed, but the Apache 2.0 license indicates it is open source. No information is provided about the maker beyond the username 'alexkstern,' and there are no claims regarding popularity, user base, or comparative standing within its class. Further details about documentation, usage instructions, or compatibility are not included in the available evidence.

code_5pct_9e18_seed1_2026-07-12_03-23-07_011612-pt is an open-source code language model checkpoint available on Hugging Face. It is designed for developers and researchers working on code generation and related AI tasks, supporting further fine-tuning and integration into custom workflows.

Code 1pct 9e18 Seed2 2026 07 12 00 08 42 554920 Pt is a machine learning model checkpoint hosted on Hugging Face. The model is trained with nanochat and represents a checkpoint at step 12,281. Its configuration specifies a sequence length of 2048, a vocabulary size of 65,536, 18 layers, 9 attention heads, 9 key-value heads, and an embedding size of 1,152. The license for this model is Apache 2.0, indicating it is available under an open-source license. Training details include the use of a matrix learning rate of 0.015 and an embedding learning rate, with a total training time of approximately 3,183 units (the unit is not specified in the evidence). The outcome metrics provided are smooth_train_loss and min_objective, along with computational statistics such as flops used and flops per token. The model is delivered as a downloadable checkpoint file from Hugging Face. No further information about its intended audience, specific applications, or integration capabilities is provided in the available evidence.

Code 1pct 1e18 Seed0 2026 07 11 20 52 14 736788 Pt is a model checkpoint available on Hugging Face, released under the Apache 2.0 license. The evidence identifies it as a trained model, specifically a checkpoint at step 3,734, and indicates it was trained with "nanochat." Details from the training configuration reveal that the model uses a sequence length of 2048, a vocabulary size of 65,536, 11 layers, 6 attention heads, and an embedding size of 768. The checkpoint is associated with a W&B run and includes several training metrics, such as smooth_train_loss and total_training_time. The model card and configuration files are accessible for download and use from the Hugging Face platform. No further details about the intended audience, specific use cases, or application domains are provided in the available evidence. The tool is positioned as a model checkpoint, but the evidence does not specify the types of tasks or problems it is designed to address beyond the information included in the training configuration and metadata. Given the available information, this checkpoint is suitable for users seeking to access or examine a model trained with the stated parameters and methods, but additional context about its capabilities or applications is not present in the evidence.

code_1pct_9e18_seed1_2026-07-11_23-13-23_046214-pt is an open-source checkpoint of a language model fine-tuned for code generation research. It is intended for AI researchers and developers working on code synthesis, completion, or related tasks.

code_1pct_9e18_seed0_2026-07-11_22-18-01_208511-ppt is a pretrained language model checkpoint for code-related tasks, released under the Apache 2.0 license on Hugging Face. It is intended for AI researchers and developers who need open-source code generation models for integration or further fine-tuning.

Code 1pct 1e18 Seed1 2026 07 11 21 00 55 672530 Pt is a machine learning model checkpoint available on Hugging Face. The checkpoint was trained using a configuration that includes a sequence length of 2048, a vocabulary size of 65,536, 11 layers, 6 attention heads, and an embedding size of 768. Specific training details are provided, such as the checkpoint being saved at step 3,734, with a smooth training loss of approximately 3.26 and a minimum objective value of about 0.98. The model was trained using a tool or framework referred to as nanochat, and additional references are made to training metrics including the total number of floating point operations and total training time. The licensing for this checkpoint is specified as Apache 2.0. The evidence does not indicate the intended use cases, target audience, or specific tasks the model is designed to address. There is no information about supported platforms, integrations, or whether the model is intended for research, code generation, or other applications. Delivery is through Hugging Face as a downloadable checkpoint file, but further usage details are not provided. Due to the limited scope of available information, only the model’s technical configuration, training details, and licensing can be confirmed.

Code 1pct 3e18 Seed1 2026 07 11 21 38 08 841300 Pt is a machine learning model checkpoint hosted on Hugging Face. The checkpoint was trained using a configuration that includes a sequence length of 2048, a vocabulary size of 65,536, 15 layers, 8 attention heads, 8 key-value heads, and an embedding size of 1024. The training process involved the use of the 'nanochat' setup, and the checkpoint was saved at step 5,735. The training utilized a total of approximately 2.97e+18 floating point operations, with a reported smooth training loss of 2.91 at the checkpoint. The model and its associated files are distributed under the Apache 2.0 license. The evidence does not specify the intended application domain for this model checkpoint, such as whether it is designed for code generation, text processing, or another specific task. Details about target users, deployment methods, or integration options are not provided. Only technical training parameters and licensing information are explicitly stated. This checkpoint is available for download and use through the Hugging Face platform, under the terms of the Apache 2.0 open-source license.

code_1pct_9e18_seed0_2026-07-11_22-18-01_208511-pt is a pretrained language model checkpoint for code-related tasks, released under the Apache 2.0 license on Hugging Face. It is intended for AI researchers and developers who need open-source code generation models for integration or further fine-tuning.