From ccd0337d259b45a8621e1932b21c102d6015ae29 Mon Sep 17 00:00:00 2001 From: ModelHub XC Date: Tue, 29 Sep 2026 17:45:18 +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: applegrew/support-125M-slm-sft Source: Original Platform --- .gitattributes | 35 + README.md | 122 + config.json | 30 + generation_config.json | 6 + model.safetensors | 3 + special_tokens_map.json | 11 + tokenizer.json | 80966 ++++++++++++++++++++++++++++++++++++++ tokenizer_config.json | 72 + 8 files changed, 81245 insertions(+) create mode 100644 .gitattributes create mode 100644 README.md create mode 100644 config.json create mode 100644 generation_config.json create mode 100644 model.safetensors create mode 100644 special_tokens_map.json create mode 100644 tokenizer.json create mode 100644 tokenizer_config.json diff --git a/.gitattributes b/.gitattributes new file mode 100644 index 0000000..a6344aa --- /dev/null +++ b/.gitattributes @@ -0,0 +1,35 @@ +*.7z filter=lfs diff=lfs merge=lfs -text +*.arrow filter=lfs diff=lfs merge=lfs -text +*.bin filter=lfs diff=lfs merge=lfs -text +*.bz2 filter=lfs diff=lfs merge=lfs -text +*.ckpt filter=lfs diff=lfs merge=lfs -text +*.ftz filter=lfs diff=lfs merge=lfs -text +*.gz filter=lfs diff=lfs merge=lfs -text +*.h5 filter=lfs diff=lfs merge=lfs -text +*.joblib filter=lfs diff=lfs merge=lfs -text +*.lfs.* filter=lfs diff=lfs merge=lfs -text +*.mlmodel filter=lfs diff=lfs merge=lfs -text +*.model filter=lfs diff=lfs merge=lfs -text +*.msgpack filter=lfs diff=lfs merge=lfs -text +*.npy filter=lfs diff=lfs merge=lfs -text +*.npz filter=lfs diff=lfs merge=lfs -text +*.onnx filter=lfs diff=lfs merge=lfs -text +*.ot filter=lfs diff=lfs merge=lfs -text +*.parquet filter=lfs diff=lfs merge=lfs -text +*.pb filter=lfs diff=lfs merge=lfs -text +*.pickle filter=lfs diff=lfs merge=lfs -text +*.pkl filter=lfs diff=lfs merge=lfs -text +*.pt filter=lfs diff=lfs merge=lfs -text +*.pth filter=lfs diff=lfs merge=lfs -text +*.rar filter=lfs diff=lfs merge=lfs -text +*.safetensors filter=lfs diff=lfs merge=lfs -text +saved_model/**/* filter=lfs diff=lfs merge=lfs -text +*.tar.* filter=lfs diff=lfs merge=lfs -text +*.tar filter=lfs diff=lfs merge=lfs -text +*.tflite filter=lfs diff=lfs merge=lfs -text +*.tgz filter=lfs diff=lfs merge=lfs -text +*.wasm filter=lfs diff=lfs merge=lfs -text +*.xz filter=lfs diff=lfs merge=lfs -text +*.zip filter=lfs diff=lfs merge=lfs -text +*.zst filter=lfs diff=lfs merge=lfs -text +*tfevents* filter=lfs diff=lfs merge=lfs -text diff --git a/README.md b/README.md new file mode 100644 index 0000000..fcbf026 --- /dev/null +++ b/README.md @@ -0,0 +1,122 @@ +--- +language: en +license: mit +tags: +- slm +- llama +- from-scratch +- it-support +- call-centre +- instruction-tuned +- sft +- raft +- retrieval-augmented +datasets: +- applegrew/support-125M-slm-base +pipeline_tag: text-generation +library_name: transformers +--- + +# Support 125M SLM - SFT (Instruction-Tuned + RAFT) + +A **125M parameter Llama-style language model** trained from scratch on ~2.6B tokens of IT support data, then instruction-tuned on ~17K examples including **RAFT (Retrieval-Augmented Fine-Tuning)** data. + +Built from the pretrained base model ([applegrew/support-125M-slm-base](https://huggingface.co/applegrew/support-125M-slm-base)). + +## Capabilities + +| Capability | Example | +|-----------|---------| +| IT troubleshooting | "My VPN keeps disconnecting" → step-by-step help | +| Casual chat | "Hi" → "Hello! How can I help you today?" | +| Follow-ups | "That didn't work" → "Let's try another approach" | +| **Grounded answers (RAFT)** | Given a KB article, answers only from it | +| **Refusals (RAFT)** | "Not in the context" → "I don't have enough information to answer" | + +## Training Data (17,002 records) + +| Source | Pairs | Method | Cost | +|--------|-------|--------|------| +| StackExchange (filtered IT) | 10,372 | Direct extraction | $0 | +| Ubuntu IRC + Gemini | 2,821 | Teacher distillation | $1.50 | +| Casual interactions | 732 | Seed + Gemini expansion | $0.04 | +| **RAFT dataset** | **3,077** | Gemini 3.5 Flash-Lite | $0.40 | +| **Total** | **17,002** | | **~$1.94** | + +### RAFT Pairs Breakdown + +| Type | Count | Behavior taught | +|------|-------|-----------------| +| Answerable (grounded) | 2,306 | Answer strictly from provided context | +| Unanswerable (refusal) | 771 | Say "not enough information" | + +## Training Details + +| Setting | Value | +|---------|-------| +| Epochs | 3 | +| Learning rate | 2e-4 (cosine decay) | +| Batch size | 8 | +| Loss masking | Assistant tokens only | +| Hardware | 1x H100 | +| **Best val loss** | **2.099** | +| **Val perplexity** | **8.83** | +| **Total SFT cost** | **~$2.20** | + +## Usage + +### Plain chat + +```python +from transformers import AutoModelForCausalLM, AutoTokenizer + +model = AutoModelForCausalLM.from_pretrained("applegrew/support-125M-slm-sft") +tokenizer = AutoTokenizer.from_pretrained("applegrew/support-125M-slm-sft") + +chat = "<|bos|><|system|>\nYou are a helpful IT support technician.<|eos|>\n<|user|>\nMy VPN keeps disconnecting every 5 minutes<|eos|>\n<|assistant|>\n" +inputs = tokenizer(chat, return_tensors="pt") +outputs = model.generate(**inputs, max_new_tokens=100, temperature=0.7, do_sample=True) +print(tokenizer.decode(outputs[0], skip_special_tokens=False)) +``` + +### RAG / Grounded (RAFT) style + +```python +context = "WiFi drops on Ubuntu 22.04. Run 'iwconfig', check Power Management, disable with 'sudo iwconfig wlan0 power off'." +question = "Why does my wifi keep dropping?" + +chat = ( + "<|bos|><|system|>\nYou are a helpful IT support technician. Answer using ONLY the " + "provided context. If the answer is not in the context, say you do not have enough " + "information to answer.<|eos|>\n" + f"<|user|>\n\n{context}\n\n\nQuestion: {question}<|eos|>\n<|assistant|>\n" +) +``` + +## Chat Template + +``` +<|bos|><|system|> +{system_prompt}<|eos|> +<|user|> +{question}<|eos|> +<|assistant|> +{answer}<|eos|> +``` + +Only the assistant's answer contributes to the loss during training. + +## Web Demo + +Try it live: [https://vercel-liart-xi.vercel.app](https://vercel-liart-xi.vercel.app) + +## Project Summary + +| Phase | Cost | Description | +|-------|------|-------------| +| Data pipeline | $0 | Clean → dedup → tokenize 2.6B IT tokens | +| Tokenizer | $0 | 16K BPE trained on corpus | +| Pretraining (6 epochs) | $31 | 125M Llama, 8x H100 | +| SFT data | ~$1.94 | Gemini distillation + filtering + RAFT | +| SFT training (3 rounds) | ~$2.20 | 1x H100 | +| **Total** | **~$35** | | diff --git a/config.json b/config.json new file mode 100644 index 0000000..dcf5b8b --- /dev/null +++ b/config.json @@ -0,0 +1,30 @@ +{ + "_name_or_path": "/root/data/checkpoints/sft", + "architectures": [ + "LlamaForCausalLM" + ], + "attention_bias": false, + "attention_dropout": 0.0, + "bos_token_id": 1, + "eos_token_id": 2, + "head_dim": 64, + "hidden_act": "silu", + "hidden_size": 768, + "initializer_range": 0.02, + "intermediate_size": 3072, + "max_position_embeddings": 1024, + "mlp_bias": false, + "model_type": "llama", + "num_attention_heads": 12, + "num_hidden_layers": 12, + "num_key_value_heads": 12, + "pretraining_tp": 1, + "rms_norm_eps": 1e-05, + "rope_scaling": null, + "rope_theta": 10000.0, + "tie_word_embeddings": true, + "torch_dtype": "bfloat16", + "transformers_version": "4.46.3", + "use_cache": true, + "vocab_size": 16384 +} diff --git a/generation_config.json b/generation_config.json new file mode 100644 index 0000000..36d1470 --- /dev/null +++ b/generation_config.json @@ -0,0 +1,6 @@ +{ + "_from_model_config": true, + "bos_token_id": 1, + "eos_token_id": 2, + 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