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Model: duyntnet/Seed-Coder-8B-Instruct-imatrix-GGUF Source: Original Platform
2026-10-18 16:16:19 +08:00
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+---
+license: other
+language:
+- en
+pipeline_tag: text-generation
+inference: false
+tags:
+- transformers
+- gguf
+- imatrix
+- Seed-Coder-8B-Instruct
+---
+
+Quantizations of https://huggingface.co/ByteDance-Seed/Seed-Coder-8B-Instruct
+
+
+### Open source inference clients/UIs
+* [llama.cpp](https://github.com/ggerganov/llama.cpp)
+* [KoboldCPP](https://github.com/LostRuins/koboldcpp)
+* [text-generation-webui](https://github.com/oobabooga/text-generation-webui)
+
+### Closed source inference clients/UIs
+* [LM Studio](https://lmstudio.ai/)
+* More will be added...
+---
+
+# From original readme
+
+We are thrilled to introduce Seed-Coder, a powerful, transparent, and parameter-efficient family of open-source code models at the 8B scale, featuring base, instruct, and reasoning variants. Seed-Coder contributes to promote the evolution of open code models through the following highlights.
+
+- **Model-centric:** Seed-Coder predominantly leverages LLMs instead of hand-crafted rules for code data filtering, minimizing manual effort in pretraining data construction.
+- **Transparent:** We openly share detailed insights into our model-centric data pipeline, including methods for curating GitHub data, commits data, and code-related web data.
+- **Powerful:** Seed-Coder achieves state-of-the-art performance among open-source models of comparable size across a diverse range of coding tasks.
+
+This repo contains the **Seed-Coder-8B-Instruct** model, which has the following features:
+- Type: Causal language models
+- Training Stage: Pretraining & Post-training
+- Data Source: Public datasets, synthetic data
+- Context Length: 32,768
+
+
+## Model Downloads
+| Model Name                  | Length | Download   |    Notes |
+|---------------------------------------------------------|--------|------------------------------------|-----------------------|
+| Seed-Coder-8B-Base           | 32K    | 🤗 [Model](https://huggingface.co/ByteDance-Seed/Seed-Coder-8B-Base)   |  Pretrained on our model-centric code data.  |
+| 👉 **Seed-Coder-8B-Instruct**  | 32K    | 🤗 [Model](https://huggingface.co/ByteDance-Seed/Seed-Coder-8B-Instruct)   |  Instruction-tuned for alignment with user intent. |
+| Seed-Coder-8B-Reasoning            | 64K    | 🤗 [Model](https://huggingface.co/ByteDance-Seed/Seed-Coder-8B-Reasoning)   |  RL trained to boost reasoning capabilities.  |
+| Seed-Coder-8B-Reasoning-bf16 | 64K    | 🤗 [Model](https://huggingface.co/ByteDance-Seed/Seed-Coder-8B-Reasoning-bf16)   |  RL trained to boost reasoning capabilities.  |
+
+## Requirements
+You will need to install the latest versions of `transformers` and `accelerate`:
+
+```bash
+pip install -U transformers accelerate
+```
+
+## Quickstart
+
+Here is a simple example demonstrating how to load the model and generate code using the Hugging Face `pipeline` API:
+
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
+
+model_id = "ByteDance-Seed/Seed-Coder-8B-Instruct"
+
+tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
+model = AutoModelForCausalLM.from_pretrained(model_id, torch_dtype=torch.bfloat16, device_map="auto", trust_remote_code=True)
+
+messages = [
+    {"role": "user", "content": "Write a quick sort algorithm."},
+]
+
+input_ids = tokenizer.apply_chat_template(
+    messages,
+    tokenize=True,
+    return_tensors="pt",
+    add_generation_prompt=True,  
+).to(model.device)
+
+outputs = model.generate(input_ids, max_new_tokens=512)
+response = tokenizer.decode(outputs[0][input_ids.shape[-1]:], skip_special_tokens=True)
+print(response)
+
+```
+
+## Evaluation
+
+Seed-Coder-8B-Instruct has been evaluated on a wide range of coding tasks, including code generation, code reasoning, code editing, and software engineering, achieving state-of-the-art performance among ~8B open-source models.
+
+|             Model             | HumanEval | MBPP | MHPP | BigCodeBench (Full) | BigCodeBench (Hard) | LiveCodeBench (2410 – 2502) |
+|:-----------------------------:|:---------:|:----:|:----:|:-------------------:|:-------------------:|:-------------------------:|
+|     CodeLlama-7B-Instruct     |    40.9   | 54.0 |  6.7 |         25.7        |         4.1         |            3.6            |
+|  DeepSeek-Coder-6.7B-Instruct |    74.4   | 74.9 | 20.0 |         43.8        |         15.5        |            9.6            |
+|      CodeQwen1.5-7B-Chat      |    83.5   | 77.7 | 17.6 |         43.6        |         15.5        |            3.0            |
+|        Yi-Coder-9B-Chat       |    82.3   | 82.0 | 26.7 |         49.0        |         17.6        |            17.5           |
+|     Llama-3.1-8B-Instruct     |    68.3   | 70.1 | 17.1 |         40.5        |         13.5        |            11.5           |
+|     OpenCoder-8B-Instruct     |    83.5   | 79.1 | 30.5 |         50.9        |         18.9        |            17.1           |
+|   Qwen2.5-Coder-7B-Instruct   |    **88.4**   | 83.5 | 26.7 |         48.8        |         20.3        |            17.3           |
+|            Qwen3-8B           |    84.8   | 77.0 | 32.8 |         51.7        |         23.0        |            23.5           |
+| Seed-Coder-8B-Instruct        |    84.8   | **85.2** | **36.2** |         **53.3**        |         **26.4**        |            **24.7**           |
+
+
+For detailed benchmark performance, please refer to our [📑 Technical Report](https://github.com/ByteDance-Seed/Seed-Coder/blob/master/Seed-Coder.pdf).