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delta_net-1.3B-100B/README.md

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+---
+library_name: transformers
+tags: []
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
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+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]

delta_net-1.3B-100B/config.json

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+{
+  "_name_or_path": "fla-hub/delta_net-1.3B-100B",
+  "architectures": [
+    "DeltaNetForCausalLM"
+  ],
+  "attn": null,
+  "attn_mode": "chunk",
+  "bos_token_id": 1,
+  "conv_size": 4,
+  "eos_token_id": 2,
+  "expand_k": 1,
+  "expand_v": 1,
+  "fuse_cross_entropy": true,
+  "fuse_norm": true,
+  "hidden_act": "swish",
+  "hidden_ratio": 4,
+  "hidden_size": 2048,
+  "initializer_range": 0.02,
+  "intermediate_size": null,
+  "max_position_embeddings": 2048,
+  "model_type": "delta_net",
+  "norm_eps": 1e-06,
+  "num_heads": 16,
+  "num_hidden_layers": 24,
+  "pad_token_id": 2,
+  "qk_activation": "silu",
+  "qk_norm": "l2",
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.48.2",
+  "use_beta": true,
+  "use_cache": true,
+  "use_gate": false,
+  "use_output_norm": true,
+  "use_short_conv": true,
+  "vocab_size": 32000
+}

delta_net-1.3B-100B/generation_config.json

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+{
+  "_from_model_config": true,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "pad_token_id": 2,
+  "transformers_version": "4.48.2"
+}

delta_net-1.3B-100B/model.safetensors

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+size 2731391664

delta_net-1.3B-100B/results

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+
+hf (pretrained=/mnt/jfzn/msj/delta_net-1.3B-100B,dtype=bfloat16), gen_kwargs: (None), limit: None, num_fewshot: None, batch_size: 4
+|     Tasks      |Version|Filter|n-shot|    Metric     |   | Value |   |Stderr|
+|----------------|------:|------|-----:|---------------|---|------:|---|------|
+|arc_challenge   |      1|none  |     0|acc            |↑  | 0.2432|±  |0.0125|
+|                |       |none  |     0|acc_norm       |↑  | 0.2679|±  |0.0129|
+|arc_easy        |      1|none  |     0|acc            |↑  | 0.5854|±  |0.0101|
+|                |       |none  |     0|acc_norm       |↑  | 0.5240|±  |0.0102|
+|hellaswag       |      1|none  |     0|acc            |↑  | 0.3961|±  |0.0049|
+|                |       |none  |     0|acc_norm       |↑  | 0.5024|±  |0.0050|
+|lambada_standard|      1|none  |     0|acc            |↑  | 0.4209|±  |0.0069|
+|                |       |none  |     0|perplexity     |↓  |15.4219|±  |0.4607|
+|piqa            |      1|none  |     0|acc            |↑  | 0.7051|±  |0.0106|
+|                |       |none  |     0|acc_norm       |↑  | 0.7035|±  |0.0107|
+|wikitext        |      2|none  |     0|bits_per_byte  |↓  | 0.7598|±  |   N/A|
+|                |       |none  |     0|byte_perplexity|↓  | 1.6933|±  |   N/A|
+|                |       |none  |     0|word_perplexity|↓  |16.7166|±  |   N/A|
+|winogrande      |      1|none  |     0|acc            |↑  | 0.5288|±  |0.0140|

delta_net-1.3B-100B/special_tokens_map.json

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+{
+  "bos_token": {
+    "content": "<s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eos_token": {
+    "content": "</s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "</s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "unk_token": {
+    "content": "<unk>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

delta_net-1.3B-100B/tokenizer.model

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+oid sha256:dadfd56d766715c61d2ef780a525ab43b8e6da4de6865bda3d95fdef5e134055
+size 493443

delta_net-1.3B-100B/tokenizer_config.json

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+{
+  "add_bos_token": true,
+  "add_eos_token": false,
+  "add_prefix_space": null,
+  "added_tokens_decoder": {
+    "0": {
+      "content": "<unk>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "1": {
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+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "2": {
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+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "additional_special_tokens": [],
+  "bos_token": "<s>",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "</s>",
+  "legacy": false,
+  "model_max_length": 1000000000000000019884624838656,
+  "pad_token": "</s>",
+  "sp_model_kwargs": {},
+  "spaces_between_special_tokens": false,
+  "tokenizer_class": "LlamaTokenizer",
+  "unk_token": "<unk>",
+  "use_default_system_prompt": false
+}

gla-1.3B-100B/.gitattributes

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gla-1.3B-100B/README.md

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+---
+datasets:
+- cerebras/SlimPajama-627B
+language:
+- en
+library_name: transformers
+license: mit
+pipeline_tag: text-generation
+tags:
+- text-generation
+- gla
+---
+
+# GLA 1.3B-100B
+
+This repository contains the `gla-1.3B-100B` model, a 1.3B parameter variant trained on 100B tokens, which was presented in the paper [Gated Linear Attention Transformers with Hardware-Efficient Training](https://huggingface.co/papers/2312.06635).
+
+## Usage
+
+This model can be easily loaded and used for text generation tasks with the Hugging Face `transformers` library:
+
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+# Load the tokenizer and model
+model_id = "fla-hub/gla-1.3B-100B"
+tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
+model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)
+
+# Example for text generation
+prompt = "Hello, my name is"
+inputs = tokenizer(prompt, return_tensors="pt")
+
+# Generate text
+outputs = model.generate(**inputs, max_new_tokens=50, do_sample=True, top_k=50, top_p=0.95, temperature=0.7)
+generated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
+
+print(generated_text)
+```
+
+## Paper and Citation
+
+If you find this work useful, please consider citing the original paper:
+
+[Gated Linear Attention Transformers with Hardware-Efficient Training](https://huggingface.co/papers/2507.06457)
+
+```bibtex
+@article{li2025systematic,
+  title={Gated Linear Attention Transformers with Hardware-Efficient Training},
+  author={Songlin Yang, Bailin Wang, Yikang Shen, Rameswar Panda, Yoon Kim},
+  journal={arXiv preprint arXiv:2312.06635},
+  year={2023},
+}
+```
+
+## Code
+
+The official codebase for the models and research, including training scripts and other checkpoints, can be found on GitHub:
+
+[https://github.com/fla-org/flash-linear-attention](https://github.com/fla-org/flash-linear-attention)

gla-1.3B-100B/config.json

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+{
+  "_name_or_path": "fla-hub/gla-1.3B-100B",
+  "architectures": [
+    "GLAForCausalLM"
+  ],
+  "attn": null,
+  "attn_mode": "chunk",
+  "bos_token_id": 1,
+  "clamp_min": null,
+  "conv_size": 4,
+  "elementwise_affine": true,
+  "eos_token_id": 2,
+  "expand_k": 0.5,
+  "expand_v": 1,
+  "feature_map": null,
+  "fuse_cross_entropy": true,
+  "fuse_norm": true,
+  "hidden_act": "swish",
+  "hidden_ratio": 4,
+  "hidden_size": 2048,
+  "initializer_range": 0.02,
+  "intermediate_size": null,
+  "max_position_embeddings": 2048,
+  "model_type": "gla",
+  "norm_eps": 1e-06,
+  "num_heads": 4,
+  "num_hidden_layers": 24,
+  "num_kv_heads": null,
+  "rms_norm_eps": 1e-06,
+  "share_conv_kernel": true,
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.48.2",
+  "use_cache": true,
+  "use_gk": true,
+  "use_gv": false,
+  "use_output_gate": true,
+  "use_short_conv": false,
+  "vocab_size": 32000
+}

gla-1.3B-100B/generation_config.json

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+{
+  "_from_model_config": true,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "transformers_version": "4.48.2"
+}

gla-1.3B-100B/model.safetensors

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gla-1.3B-100B/results

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+[2025-12-19T06:36:25.817275328Z] hf (pretrained=/mnt/jfzn/msj/download_model/gla-1.3B-100B,dtype=bfloat16), gen_kwargs: (None), limit: None, num_fewshot: None, batch_size: 4
+[2025-12-19T06:36:26.819630673Z] |     Tasks      |Version|Filter|n-shot|    Metric     |   | Value |   |Stderr|
+[2025-12-19T06:36:26.819759914Z] |----------------|------:|------|-----:|---------------|---|------:|---|------|
+[2025-12-19T06:36:26.819885571Z] |arc_challenge   |      1|none  |     0|acc            |↑  | 0.2355|±  |0.0124|
+[2025-12-19T06:36:26.820004149Z] |                |       |none  |     0|acc_norm       |↑  | 0.2773|±  |0.0131|
+[2025-12-19T06:36:26.820116656Z] |arc_easy        |      1|none  |     0|acc            |↑  | 0.5497|±  |0.0102|
+[2025-12-19T06:36:26.820232966Z] |                |       |none  |     0|acc_norm       |↑  | 0.4865|±  |0.0103|
+[2025-12-19T06:36:26.820345916Z] |hellaswag       |      1|none  |     0|acc            |↑  | 0.3900|±  |0.0049|
+[2025-12-19T06:36:26.820459186Z] |                |       |none  |     0|acc_norm       |↑  | 0.4895|±  |0.0050|
+[2025-12-19T06:36:26.820576807Z] |lambada_standard|      1|none  |     0|acc            |↑  | 0.4000|±  |0.0068|
+[2025-12-19T06:36:26.820694476Z] |                |       |none  |     0|perplexity     |↓  |19.6484|±  |0.6563|
+[2025-12-19T06:36:26.820808985Z] |piqa            |      1|none  |     0|acc            |↑  | 0.6975|±  |0.0107|
+[2025-12-19T06:36:26.820921305Z] |                |       |none  |     0|acc_norm       |↑  | 0.7002|±  |0.0107|
+[2025-12-19T06:36:26.821034324Z] |wikitext        |      2|none  |     0|bits_per_byte  |↓  | 0.7738|±  |   N/A|
+[2025-12-19T06:36:26.821143959Z] |                |       |none  |     0|byte_perplexity|↓  | 1.7098|±  |   N/A|
+[2025-12-19T06:36:26.821256980Z] |                |       |none  |     0|word_perplexity|↓  |17.6044|±  |   N/A|
+[2025-12-19T06:36:26.821366477Z] |winogrande      |      1|none  |     0|acc            |↑  | 0.5430|±  |0.0140|
+[2025-12-19T06:36:26.821478938Z] 

gla-1.3B-100B/special_tokens_map.json

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+  }
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gla-1.3B-100B/tokenizer_config.json

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+  "model_max_length": 1000000000000000019884624838656,
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+  "sp_model_kwargs": {},
+  "spaces_between_special_tokens": false,
+  "tokenizer_class": "LlamaTokenizer",
+  "unk_token": "<unk>",
+  "use_default_system_prompt": false
+}

hgrn2-1.3B-100B/.gitattributes

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hgrn2-1.3B-100B/README.md

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+---
+language:
+- en
+tags:
+- text-generation
+- hgrn2
+license: mit
+datasets:
+- cerebras/SlimPajama-627B
+library_name: fla
+---

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+|     Tasks      |Version|Filter|n-shot|    Metric     |   | Value |   |Stderr|
+|----------------|------:|------|-----:|---------------|---|------:|---|------|
+|arc_challenge   |      1|none  |     0|acc            |↑  | 0.2517|±  |0.0127|
+|                |       |none  |     0|acc_norm       |↑  | 0.2799|±  |0.0131|
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+|                |       |none  |     0|acc_norm       |↑  | 0.5253|±  |0.0102|
+|hellaswag       |      1|none  |     0|acc            |↑  | 0.4036|±  |0.0049|
+|                |       |none  |     0|acc_norm       |↑  | 0.5190|±  |0.0050|
+|lambada_standard|      1|none  |     0|acc            |↑  | 0.4236|±  |0.0069|
+|                |       |none  |     0|perplexity     |↓  |15.5834|±  |0.4671|
+|piqa            |      1|none  |     0|acc            |↑  | 0.7127|±  |0.0106|
+|                |       |none  |     0|acc_norm       |↑  | 0.7089|±  |0.0106|
+|wikitext        |      2|none  |     0|bits_per_byte  |↓  | 0.7635|±  |   N/A|
+|                |       |none  |     0|byte_perplexity|↓  | 1.6976|±  |   N/A|
+|                |       |none  |     0|word_perplexity|↓  |16.9457|±  |   N/A|
+|winogrande      |      1|none  |     0|acc            |↑  | 0.5280|±  |0.0140|

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retnet-1.3B-100B/README.md

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+---
+language:
+- en
+tags:
+- text-generation
+- retnet
+license: mit
+datasets:
+- cerebras/SlimPajama-627B
+library_name: fla
+---

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retnet-1.3B-100B/results

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+|     Tasks      |Version|Filter|n-shot|    Metric     |   | Value |   |Stderr|
+|----------------|------:|------|-----:|---------------|---|------:|---|------|
+|arc_challenge   |      1|none  |     0|acc            |↑  | 0.2389|±  |0.0125|
+|                |       |none  |     0|acc_norm       |↑  | 0.2662|±  |0.0129|
+|arc_easy        |      1|none  |     0|acc            |↑  | 0.5741|±  |0.0101|
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+|                |       |none  |     0|perplexity     |↓  |21.9744|±  |0.7178|
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+|                |       |none  |     0|word_perplexity|↓  |18.1786|±  |   N/A|
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transformer-1.3B-100B/README.md

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+---
+language:
+- en
+tags:
+- text-generation
+- transformer++
+license: mit
+datasets:
+- cerebras/SlimPajama-627B
+library_name: fla
+---