Initial release: merged fp16 model + model card
Browse files- .gitattributes +1 -0
- README.md +219 -0
- chat_template.jinja +54 -0
- config.json +81 -0
- generation_config.json +14 -0
- model-00001-of-00008.safetensors +3 -0
- model-00002-of-00008.safetensors +3 -0
- model-00003-of-00008.safetensors +3 -0
- model-00004-of-00008.safetensors +3 -0
- model-00005-of-00008.safetensors +3 -0
- model-00006-of-00008.safetensors +3 -0
- model-00007-of-00008.safetensors +3 -0
- model-00008-of-00008.safetensors +3 -0
- model.safetensors.index.json +587 -0
- tokenizer.json +3 -0
- tokenizer_config.json +29 -0
.gitattributes
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| 1 |
+
---
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| 2 |
+
license: apache-2.0
|
| 3 |
+
base_model: Qwen/Qwen2.5-Coder-14B-Instruct
|
| 4 |
+
tags:
|
| 5 |
+
- csharp
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| 6 |
+
- dotnet
|
| 7 |
+
- code
|
| 8 |
+
- fine-tuned
|
| 9 |
+
- dpo
|
| 10 |
+
- qlora
|
| 11 |
+
- coding-assistant
|
| 12 |
+
- aspnet
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| 13 |
+
- entity-framework
|
| 14 |
+
language:
|
| 15 |
+
- en
|
| 16 |
+
pipeline_tag: text-generation
|
| 17 |
+
library_name: transformers
|
| 18 |
+
model-index:
|
| 19 |
+
- name: dotnet-coder-14b
|
| 20 |
+
results:
|
| 21 |
+
- task:
|
| 22 |
+
type: text-generation
|
| 23 |
+
name: C# Code Generation
|
| 24 |
+
metrics:
|
| 25 |
+
- name: Compile Rate (30 prompts)
|
| 26 |
+
type: accuracy
|
| 27 |
+
value: 97
|
| 28 |
+
- name: Compile Rate Holdout (30 fresh prompts)
|
| 29 |
+
type: accuracy
|
| 30 |
+
value: 97
|
| 31 |
+
- name: Expert Knowledge
|
| 32 |
+
type: accuracy
|
| 33 |
+
value: 100
|
| 34 |
+
- name: C# 13/14 Knowledge
|
| 35 |
+
type: accuracy
|
| 36 |
+
value: 100
|
| 37 |
+
---
|
| 38 |
+
|
| 39 |
+
# dotnet-coder-14b
|
| 40 |
+
|
| 41 |
+
**The most capable open-source C#/.NET coding model.** Fine-tuned from Qwen2.5-Coder-14B-Instruct using SFT + iterative DPO with compile verification.
|
| 42 |
+
|
| 43 |
+
A 14B parameter model that outperforms Qwen2.5-Coder-32B and Qwen2.5-72B on C# code generation, expert .NET knowledge, and modern C# language features — while running on a single consumer GPU.
|
| 44 |
+
|
| 45 |
+
## Highlights
|
| 46 |
+
|
| 47 |
+
- **97% compile rate** — generated code compiles with `dotnet build` straight out of the model
|
| 48 |
+
- **Perfect expert knowledge** (10/10) — knows ConcurrentDictionary gotchas, async void dangers, N+1 queries, EF Core pitfalls, DI lifetime bugs, and more
|
| 49 |
+
- **Perfect C# 13/14 knowledge** (10/10) — field keyword, extension members, params collections, partial properties
|
| 50 |
+
- **Beats 72B models** — outperforms Qwen2.5-72B (5x larger) on C# tasks
|
| 51 |
+
- **Runs locally** — Q4_K_M quantization fits in ~8GB VRAM (RTX 3080+, Apple M2 Pro+)
|
| 52 |
+
|
| 53 |
+
## Benchmarks
|
| 54 |
+
|
| 55 |
+
### Compile Rate (code compiles with `dotnet build`)
|
| 56 |
+
|
| 57 |
+
| Model | Parameters | Compile Rate | Holdout (fresh prompts) |
|
| 58 |
+
|---|---|---|---|
|
| 59 |
+
| **dotnet-coder-14b** | **14B** | **97%** | **97%** |
|
| 60 |
+
| Qwen2.5-Coder-14B-Instruct | 14B | 83% | 93% |
|
| 61 |
+
| Qwen2.5-72B-Instruct | 72B | 80% | 80% |
|
| 62 |
+
| Qwen2.5-Coder-32B-Instruct | 32B | 80% | 87% |
|
| 63 |
+
| Qwen2.5-Coder-7B-Instruct | 7B | 57% | 67% |
|
| 64 |
+
| DeepSeek-R1-Distill-Qwen-14B | 14B | 10% | 13% |
|
| 65 |
+
|
| 66 |
+
### Expert .NET Knowledge (10 expert gotcha questions + 10 C# 13/14 questions)
|
| 67 |
+
|
| 68 |
+
| Model | Parameters | Expert Gotchas | C# 13/14 Features |
|
| 69 |
+
|---|---|---|---|
|
| 70 |
+
| **dotnet-coder-14b** | **14B** | **10/10** | **10/10** |
|
| 71 |
+
| Qwen2.5-72B-Instruct | 72B | 9/10 | 10/10 |
|
| 72 |
+
| Qwen2.5-Coder-14B-Instruct | 14B | 8/10 | 10/10 |
|
| 73 |
+
| Qwen2.5-Coder-32B-Instruct | 32B | 6/10 | 10/10 |
|
| 74 |
+
| DeepSeek-R1-Distill-Qwen-14B | 14B | 3/10 | 5/10 |
|
| 75 |
+
|
| 76 |
+
### Complex Multi-Class Tasks (10 tasks requiring 3-6 interacting classes)
|
| 77 |
+
|
| 78 |
+
| Model | Parameters | First Try | With Retry |
|
| 79 |
+
|---|---|---|---|
|
| 80 |
+
| **dotnet-coder-14b** | **14B** | **70-90%** | **90%+** |
|
| 81 |
+
|
| 82 |
+
Tasks include: CQRS with dispatcher, event sourcing, fluent validation framework, resilience pipeline, state machines, plugin systems, and more.
|
| 83 |
+
|
| 84 |
+
## What This Model Is Good At
|
| 85 |
+
|
| 86 |
+
- Writing complete, compilable C# classes and files
|
| 87 |
+
- ASP.NET Core middleware, controllers, and minimal APIs
|
| 88 |
+
- Entity Framework Core queries, configurations, and patterns
|
| 89 |
+
- Design patterns implemented in idiomatic C#
|
| 90 |
+
- Modern C# features (records, primary constructors, collection expressions, pattern matching)
|
| 91 |
+
- Explaining C# gotchas and .NET internals
|
| 92 |
+
- Code that's ready to use — no unnecessary boilerplate or explanation
|
| 93 |
+
|
| 94 |
+
## Usage
|
| 95 |
+
|
| 96 |
+
### With Transformers
|
| 97 |
+
|
| 98 |
+
```python
|
| 99 |
+
from transformers import AutoModelForCausalLM, AutoTokenizer
|
| 100 |
+
import torch
|
| 101 |
+
|
| 102 |
+
model = AutoModelForCausalLM.from_pretrained(
|
| 103 |
+
"zipaltrivedi/dotnet-coder-14b",
|
| 104 |
+
torch_dtype=torch.float16,
|
| 105 |
+
device_map="auto",
|
| 106 |
+
)
|
| 107 |
+
tokenizer = AutoTokenizer.from_pretrained("zipaltrivedi/dotnet-coder-14b")
|
| 108 |
+
|
| 109 |
+
messages = [
|
| 110 |
+
{"role": "system", "content": "You are an expert C# and .NET developer. Write complete, compilable C# code."},
|
| 111 |
+
{"role": "user", "content": "Write a thread-safe LRU cache with generic key and value types in C#."},
|
| 112 |
+
]
|
| 113 |
+
|
| 114 |
+
text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
|
| 115 |
+
inputs = tokenizer(text, return_tensors="pt").to(model.device)
|
| 116 |
+
output = model.generate(**inputs, max_new_tokens=1024, temperature=0.2, top_p=0.9)
|
| 117 |
+
print(tokenizer.decode(output[0][inputs["input_ids"].shape[1]:], skip_special_tokens=True))
|
| 118 |
+
```
|
| 119 |
+
|
| 120 |
+
### With Ollama
|
| 121 |
+
|
| 122 |
+
```bash
|
| 123 |
+
ollama run zipaltrivedi/dotnet-coder-14b
|
| 124 |
+
```
|
| 125 |
+
|
| 126 |
+
### With llama.cpp
|
| 127 |
+
|
| 128 |
+
```bash
|
| 129 |
+
./llama-cli -m dotnet-coder-14b-Q4_K_M.gguf -p "Write a C# class for..." --temp 0.2
|
| 130 |
+
```
|
| 131 |
+
|
| 132 |
+
### With LM Studio / Jan / GPT4All
|
| 133 |
+
|
| 134 |
+
Download the GGUF file matching your hardware from the Files tab and load it in your preferred UI.
|
| 135 |
+
|
| 136 |
+
## GGUF Quantizations
|
| 137 |
+
|
| 138 |
+
| Quantization | Size | Min RAM | Recommended For |
|
| 139 |
+
|---|---|---|---|
|
| 140 |
+
| Q8_0 | ~15GB | 16GB+ | Best quality — RTX 4090, A100, M3 Max 36GB |
|
| 141 |
+
| Q6_K | ~12GB | 14GB+ | High quality — RTX 4080, M2 Max 32GB |
|
| 142 |
+
| **Q4_K_M** | **~8GB** | **10GB+** | **Recommended — RTX 3080/4070, M2 Pro 16GB** |
|
| 143 |
+
| Q4_K_S | ~7.5GB | 9GB+ | Slightly smaller — M1 Pro 16GB |
|
| 144 |
+
| Q3_K_M | ~6.5GB | 8GB+ | Budget GPU, Apple M1/M2 8GB |
|
| 145 |
+
| IQ4_XS | ~7GB | 9GB+ | Good quality at small size |
|
| 146 |
+
| Q2_K | ~5GB | 6GB+ | CPU-only inference, minimum viable |
|
| 147 |
+
|
| 148 |
+
## Training Details
|
| 149 |
+
|
| 150 |
+
### Method
|
| 151 |
+
|
| 152 |
+
1. **SFT (Supervised Fine-Tuning)**: QLoRA 4-bit, rank 64, alpha 128, 2 epochs on 107K C# training records
|
| 153 |
+
2. **DPO (Direct Preference Optimization)**: 3 iterative rounds using `dotnet build` compilation as the reward signal
|
| 154 |
+
- Round 1: 126 preference pairs (compilable vs non-compilable) — 57% → 73%
|
| 155 |
+
- Round 2: 382 pairs with stronger signal — 73% → 87%
|
| 156 |
+
- Round 3: 850 pairs from improved model — 87% → 97%
|
| 157 |
+
|
| 158 |
+
### Dataset (107K records)
|
| 159 |
+
|
| 160 |
+
| Source | Records | Description |
|
| 161 |
+
|---|---|---|
|
| 162 |
+
| Expert C# knowledge | 54,443 | Curated Q&A covering gotchas, patterns, best practices, version-specific features |
|
| 163 |
+
| Compile-verified repos | 35,736 | Self-contained C# files from 140 GitHub repos, filtered and verified |
|
| 164 |
+
| .NET runtime source | 12,352 | Code from dotnet/runtime, aspnetcore, and other core .NET repos |
|
| 165 |
+
| Synthetic examples | 4,906 | C# 13/14 features, debugging pairs, code review examples |
|
| 166 |
+
|
| 167 |
+
### Infrastructure
|
| 168 |
+
|
| 169 |
+
- **Hardware**: RunPod A100 80GB SXM
|
| 170 |
+
- **SFT training**: ~13 hours
|
| 171 |
+
- **DPO training**: ~2 hours total (3 rounds)
|
| 172 |
+
- **Total cost**: ~$60
|
| 173 |
+
|
| 174 |
+
### Hyperparameters
|
| 175 |
+
|
| 176 |
+
- **SFT**: lr=2e-4, batch=16 (2x8 grad accum), warmup 3%, cosine schedule, packing enabled
|
| 177 |
+
- **DPO**: lr=5e-5, beta=0.3, batch=8 (2x4 grad accum), 3 epochs per round
|
| 178 |
+
|
| 179 |
+
## Evaluation Methodology
|
| 180 |
+
|
| 181 |
+
All compile tests use actual `dotnet build` with .NET 8 SDK against a project with common NuGet packages (EF Core, ASP.NET Core, Microsoft.Extensions). No manual evaluation — pass/fail is binary based on compiler exit code.
|
| 182 |
+
|
| 183 |
+
Expert knowledge and C# version tests are evaluated by checking whether the response contains code examples and addresses the core question accurately.
|
| 184 |
+
|
| 185 |
+
## Limitations
|
| 186 |
+
|
| 187 |
+
- **Optimized for single-file code generation** — for multi-project solutions, use as a component alongside an agent framework
|
| 188 |
+
- **Concise by design** — gives direct answers with code, not step-by-step tutorials. Best for experienced developers and coding agents
|
| 189 |
+
- **English only** — trained on English C# content
|
| 190 |
+
- **14B parameter model** — for extremely complex architectural decisions, larger models may provide more nuanced analysis
|
| 191 |
+
|
| 192 |
+
## Use Cases
|
| 193 |
+
|
| 194 |
+
- **Coding agent backend** — serve via OpenAI-compatible API for use with OpenCode, Continue, Cursor, Claude Code
|
| 195 |
+
- **Local code assistant** — run with Ollama or LM Studio for offline C# development
|
| 196 |
+
- **CI/CD code generation** — generate boilerplate, tests, and implementations in automated pipelines
|
| 197 |
+
- **Learning tool** — get accurate, concise answers about C# patterns and .NET internals
|
| 198 |
+
|
| 199 |
+
## License
|
| 200 |
+
|
| 201 |
+
Apache 2.0 (same as base model Qwen2.5-Coder-14B-Instruct)
|
| 202 |
+
|
| 203 |
+
## Citation
|
| 204 |
+
|
| 205 |
+
```bibtex
|
| 206 |
+
@misc{dotnet-coder-14b,
|
| 207 |
+
author = {Zipal Trivedi},
|
| 208 |
+
title = {dotnet-coder-14b: A C#/.NET Specialist Language Model},
|
| 209 |
+
year = {2026},
|
| 210 |
+
publisher = {HuggingFace},
|
| 211 |
+
url = {https://huggingface.co/zipaltrivedi/dotnet-coder-14b}
|
| 212 |
+
}
|
| 213 |
+
```
|
| 214 |
+
|
| 215 |
+
## Acknowledgments
|
| 216 |
+
|
| 217 |
+
- Base model: [Qwen2.5-Coder-14B-Instruct](https://huggingface.co/Qwen/Qwen2.5-Coder-14B-Instruct) by Alibaba
|
| 218 |
+
- Training framework: [Unsloth](https://github.com/unslothai/unsloth)
|
| 219 |
+
- Training data sources: The Stack (permissive licenses), StackOverflow (CC-BY-SA), Microsoft Learn (CC-BY-4.0), GitHub repos (Apache/MIT licensed)
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{%- if tools %}
|
| 2 |
+
{{- '<|im_start|>system\n' }}
|
| 3 |
+
{%- if messages[0]['role'] == 'system' %}
|
| 4 |
+
{{- messages[0]['content'] }}
|
| 5 |
+
{%- else %}
|
| 6 |
+
{{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}
|
| 7 |
+
{%- endif %}
|
| 8 |
+
{{- "\n\n# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
|
| 9 |
+
{%- for tool in tools %}
|
| 10 |
+
{{- "\n" }}
|
| 11 |
+
{{- tool | tojson }}
|
| 12 |
+
{%- endfor %}
|
| 13 |
+
{{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
|
| 14 |
+
{%- else %}
|
| 15 |
+
{%- if messages[0]['role'] == 'system' %}
|
| 16 |
+
{{- '<|im_start|>system\n' + messages[0]['content'] + '<|im_end|>\n' }}
|
| 17 |
+
{%- else %}
|
| 18 |
+
{{- '<|im_start|>system\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\n' }}
|
| 19 |
+
{%- endif %}
|
| 20 |
+
{%- endif %}
|
| 21 |
+
{%- for message in messages %}
|
| 22 |
+
{%- if (message.role == "user") or (message.role == "system" and not loop.first) or (message.role == "assistant" and not message.tool_calls) %}
|
| 23 |
+
{{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
|
| 24 |
+
{%- elif message.role == "assistant" %}
|
| 25 |
+
{{- '<|im_start|>' + message.role }}
|
| 26 |
+
{%- if message.content %}
|
| 27 |
+
{{- '\n' + message.content }}
|
| 28 |
+
{%- endif %}
|
| 29 |
+
{%- for tool_call in message.tool_calls %}
|
| 30 |
+
{%- if tool_call.function is defined %}
|
| 31 |
+
{%- set tool_call = tool_call.function %}
|
| 32 |
+
{%- endif %}
|
| 33 |
+
{{- '\n<tool_call>\n{"name": "' }}
|
| 34 |
+
{{- tool_call.name }}
|
| 35 |
+
{{- '", "arguments": ' }}
|
| 36 |
+
{{- tool_call.arguments | tojson }}
|
| 37 |
+
{{- '}\n</tool_call>' }}
|
| 38 |
+
{%- endfor %}
|
| 39 |
+
{{- '<|im_end|>\n' }}
|
| 40 |
+
{%- elif message.role == "tool" %}
|
| 41 |
+
{%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != "tool") %}
|
| 42 |
+
{{- '<|im_start|>user' }}
|
| 43 |
+
{%- endif %}
|
| 44 |
+
{{- '\n<tool_response>\n' }}
|
| 45 |
+
{{- message.content }}
|
| 46 |
+
{{- '\n</tool_response>' }}
|
| 47 |
+
{%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
|
| 48 |
+
{{- '<|im_end|>\n' }}
|
| 49 |
+
{%- endif %}
|
| 50 |
+
{%- endif %}
|
| 51 |
+
{%- endfor %}
|
| 52 |
+
{%- if add_generation_prompt %}
|
| 53 |
+
{{- '<|im_start|>assistant\n' }}
|
| 54 |
+
{%- endif %}
|
config.json
ADDED
|
@@ -0,0 +1,81 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"architectures": [
|
| 3 |
+
"Qwen2ForCausalLM"
|
| 4 |
+
],
|
| 5 |
+
"attention_dropout": 0.0,
|
| 6 |
+
"bos_token_id": 151643,
|
| 7 |
+
"dtype": "float16",
|
| 8 |
+
"eos_token_id": 151645,
|
| 9 |
+
"hidden_act": "silu",
|
| 10 |
+
"hidden_size": 5120,
|
| 11 |
+
"initializer_range": 0.02,
|
| 12 |
+
"intermediate_size": 13824,
|
| 13 |
+
"layer_types": [
|
| 14 |
+
"full_attention",
|
| 15 |
+
"full_attention",
|
| 16 |
+
"full_attention",
|
| 17 |
+
"full_attention",
|
| 18 |
+
"full_attention",
|
| 19 |
+
"full_attention",
|
| 20 |
+
"full_attention",
|
| 21 |
+
"full_attention",
|
| 22 |
+
"full_attention",
|
| 23 |
+
"full_attention",
|
| 24 |
+
"full_attention",
|
| 25 |
+
"full_attention",
|
| 26 |
+
"full_attention",
|
| 27 |
+
"full_attention",
|
| 28 |
+
"full_attention",
|
| 29 |
+
"full_attention",
|
| 30 |
+
"full_attention",
|
| 31 |
+
"full_attention",
|
| 32 |
+
"full_attention",
|
| 33 |
+
"full_attention",
|
| 34 |
+
"full_attention",
|
| 35 |
+
"full_attention",
|
| 36 |
+
"full_attention",
|
| 37 |
+
"full_attention",
|
| 38 |
+
"full_attention",
|
| 39 |
+
"full_attention",
|
| 40 |
+
"full_attention",
|
| 41 |
+
"full_attention",
|
| 42 |
+
"full_attention",
|
| 43 |
+
"full_attention",
|
| 44 |
+
"full_attention",
|
| 45 |
+
"full_attention",
|
| 46 |
+
"full_attention",
|
| 47 |
+
"full_attention",
|
| 48 |
+
"full_attention",
|
| 49 |
+
"full_attention",
|
| 50 |
+
"full_attention",
|
| 51 |
+
"full_attention",
|
| 52 |
+
"full_attention",
|
| 53 |
+
"full_attention",
|
| 54 |
+
"full_attention",
|
| 55 |
+
"full_attention",
|
| 56 |
+
"full_attention",
|
| 57 |
+
"full_attention",
|
| 58 |
+
"full_attention",
|
| 59 |
+
"full_attention",
|
| 60 |
+
"full_attention",
|
| 61 |
+
"full_attention"
|
| 62 |
+
],
|
| 63 |
+
"max_position_embeddings": 32768,
|
| 64 |
+
"max_window_layers": 48,
|
| 65 |
+
"model_type": "qwen2",
|
| 66 |
+
"num_attention_heads": 40,
|
| 67 |
+
"num_hidden_layers": 48,
|
| 68 |
+
"num_key_value_heads": 8,
|
| 69 |
+
"pad_token_id": null,
|
| 70 |
+
"rms_norm_eps": 1e-06,
|
| 71 |
+
"rope_parameters": {
|
| 72 |
+
"rope_theta": 1000000.0,
|
| 73 |
+
"rope_type": "default"
|
| 74 |
+
},
|
| 75 |
+
"sliding_window": null,
|
| 76 |
+
"tie_word_embeddings": false,
|
| 77 |
+
"transformers_version": "5.5.1",
|
| 78 |
+
"use_cache": true,
|
| 79 |
+
"use_sliding_window": false,
|
| 80 |
+
"vocab_size": 152064
|
| 81 |
+
}
|
generation_config.json
ADDED
|
@@ -0,0 +1,14 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"bos_token_id": 151643,
|
| 3 |
+
"do_sample": true,
|
| 4 |
+
"eos_token_id": [
|
| 5 |
+
151645,
|
| 6 |
+
151643
|
| 7 |
+
],
|
| 8 |
+
"pad_token_id": 151643,
|
| 9 |
+
"repetition_penalty": 1.05,
|
| 10 |
+
"temperature": 0.7,
|
| 11 |
+
"top_k": 20,
|
| 12 |
+
"top_p": 0.8,
|
| 13 |
+
"transformers_version": "5.5.1"
|
| 14 |
+
}
|
model-00001-of-00008.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:b1dc539e8813c01021a103b42e997f8b11a323600d3f266acb94a35fc481b94d
|
| 3 |
+
size 3947935624
|
model-00002-of-00008.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:88be59f3c221466694c62da2911b67622da1a5cb391852f920aea37977a23a51
|
| 3 |
+
size 3995340408
|
model-00003-of-00008.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:940a2e98fb97199d18197bf435ceac9f9a9ebd57ab28e55ef6b3f2ce7193bca1
|
| 3 |
+
size 3979622536
|
model-00004-of-00008.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:6fe843541c773202330c76d20a01083407b9338a97cda4026968483a1f8f35b9
|
| 3 |
+
size 3995327992
|
model-00005-of-00008.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:950c2ad9d81cc833b40c33dddb213683fd9859402357b5466efb013189cde597
|
| 3 |
+
size 3995327976
|
model-00006-of-00008.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:82a2d927c9e541d8eb3577874ee7a7286ce85d0df271e8de723ef721aafbcdfe
|
| 3 |
+
size 3995340496
|
model-00007-of-00008.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:c3080453fadcba0c9cc66f2a78213520e07d0821eca84b698785a0a9518a2905
|
| 3 |
+
size 3979622552
|
model-00008-of-00008.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:1852809906a34ecb329aaef3f3970f7b951c8e4f812375bca278f980d32930aa
|
| 3 |
+
size 1651615744
|
model.safetensors.index.json
ADDED
|
@@ -0,0 +1,587 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
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|
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|
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|
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|
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tokenizer_config.json
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