Add HF + vLLM compatible EasySell AI model

README.md

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+---
+language:
+- en
+- hi
+tags:
+- tool-calling
+- shopping-assistant
+- causal-lm
+- custom-architecture
+license: mit
+---
+
+# 🛍️ EasySell AI — SLM Tool Calling Model
+
+A custom 101M parameter GPT model trained to output structured JSON tool calls
+for a WhatsApp e-commerce shopping assistant.
+
+## Architecture
+- **Type:** Custom GPT (Decoder-only Transformer)
+- **Parameters:** ~101M
+- **Layers:** 14 | **Heads:** 12 | **Embedding dim:** 768
+- **Context length:** 1024 tokens
+- **Vocab size:** 8000 (BPE)
+- **Trained on:** Kaggle P100, 3 epochs, loss ~0.016
+- **Attention:** `scaled_dot_product_attention` (vLLM compatible)
+
+## Quick Start
+
+```bash
+pip install transformers tokenizers torch
+```
+
+```python
+import torch
+from transformers import AutoModelForCausalLM, AutoConfig
+from tokenizers import Tokenizer
+from huggingface_hub import hf_hub_download
+
+# Load model
+model = AutoModelForCausalLM.from_pretrained(
+    "TanishqV03/easysellhfvllm",
+    trust_remote_code=True,
+)
+model.eval()
+
+# Load tokenizer
+tok_path  = hf_hub_download("TanishqV03/easysellhfvllm", "tokenizer.json")
+tokenizer = Tokenizer.from_file(tok_path)
+EOS_ID    = tokenizer.token_to_id("[EOS]")
+
+# Run inference
+prompt = "i want bag pack"
+ids    = tokenizer.encode("[BOS] " + prompt).ids
+x      = torch.tensor([ids])
+gen    = model.generate_tool_call(x, eos_token_id=EOS_ID)
+print(tokenizer.decode(gen))
+# → {"tool": "add_to_cart_tool", "parameters": {"product": "bag pack", "quantity": 1}}
+```
+
+## Supported Tools (12)
+| Tool | Fires when |
+|------|------------|
+| `search_catalog_by_text_tool` | Product search, availability checks |
+| `add_to_cart_tool` | Buy / add any product |
+| `get_checkout_link_tool` | Checkout, pay now |
+| `get_instant_checkout_link_tool` | Instant buy / direct purchase |
+| `list_all_products_tool` | Show catalog |
+| `update_order_address_tool` | Change delivery address |
+| `view_cart_tool` | Show cart |
+| `update_cart_item_tool` | Change cart item quantity |
+| `remove_from_cart_tool` | Remove specific cart item |
+| `clear_cart_tool` | Empty entire cart |
+| `clear_out_of_stock_items_tool` | Remove unavailable items |
+| `get_order_status_tool` | Order tracking |
+
+## Hinglish Support
+- `"mujhe shawl chahiye"` → `add_to_cart_tool`
+- `"cart dikhao"` → `view_cart_tool`
+- `"mobile ki link bhejo"` → `search_catalog_by_text_tool`
+
+## vLLM Usage
+```python
+from vllm import LLM
+llm = LLM(model="TanishqV03/easysellhfvllm", trust_remote_code=True)
+```
+
+Built by [Tanishq Vemaraju](https://huggingface.co/TanishqV03) — EasySell AI WhatsApp e-commerce assistant.

config.json

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+{
+  "architectures": [
+    "EasySellForCausalLM"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "bos_token_id": 1,
+  "dtype": "float32",
+  "eos_token_id": 2,
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "max_position_embeddings": 1024,
+  "model_type": "easysell",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 14,
+  "pad_token_id": 0,
+  "transformers_version": "5.0.0",
+  "vocab_size": 856,
+  "auto_map": {
+    "AutoConfig": "configuration_easysell.EasySellConfig",
+    "AutoModelForCausalLM": "modeling_easysell.EasySellForCausalLM"
+  }
+}

configuration_easysell.py

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+from transformers import PretrainedConfig
+
+
+class EasySellConfig(PretrainedConfig):
+    """
+    Config for EasySell AI causal LM.
+    Field names follow HuggingFace conventions for maximum compatibility.
+    """
+    model_type = "easysell"
+
+    def __init__(
+        self,
+        vocab_size                   = 8000,
+        max_position_embeddings      = 1024,   # = block_size
+        num_hidden_layers            = 14,     # = n_layer
+        num_attention_heads          = 12,     # = n_head
+        hidden_size                  = 768,    # = n_embd
+        hidden_dropout_prob          = 0.1,
+        attention_probs_dropout_prob = 0.1,
+        pad_token_id                 = 0,
+        bos_token_id                 = 1,
+        eos_token_id                 = 2,
+        **kwargs,
+    ):
+        self.vocab_size                   = vocab_size
+        self.max_position_embeddings      = max_position_embeddings
+        self.num_hidden_layers            = num_hidden_layers
+        self.num_attention_heads          = num_attention_heads
+        self.hidden_size                  = hidden_size
+        self.hidden_dropout_prob          = hidden_dropout_prob
+        self.attention_probs_dropout_prob = attention_probs_dropout_prob
+        super().__init__(
+            pad_token_id = pad_token_id,
+            bos_token_id = bos_token_id,
+            eos_token_id = eos_token_id,
+            **kwargs,
+        )

generation_config.json

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+{
+  "_from_model_config": true,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "output_attentions": false,
+  "output_hidden_states": false,
+  "pad_token_id": 0,
+  "transformers_version": "5.0.0"
+}

model.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:409bf0851d689616b4050d7a61d1dfdddf7befc7891e587d42fae93e015c6011
+size 405349152

modeling_easysell.py

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+import math
+import torch
+import torch.nn as nn
+import torch.nn.functional as F
+from transformers import PreTrainedModel
+from transformers.generation import GenerationMixin
+from transformers.modeling_outputs import CausalLMOutputWithPast
+from .configuration_easysell import EasySellConfig
+
+
+class EasySellAttention(nn.Module):
+    """Causal self-attention — vLLM compatible via scaled_dot_product_attention."""
+
+    def __init__(self, config: EasySellConfig):
+        super().__init__()
+        assert config.hidden_size % config.num_attention_heads == 0
+        self.num_heads = config.num_attention_heads
+        self.head_dim  = config.hidden_size // config.num_attention_heads
+        self.c_attn    = nn.Linear(config.hidden_size, 3 * config.hidden_size)
+        self.c_proj    = nn.Linear(config.hidden_size, config.hidden_size)
+        self.attn_drop = config.attention_probs_dropout_prob
+        self.resid_drop = nn.Dropout(config.hidden_dropout_prob)
+
+    def forward(self, x, attention_mask=None):
+        B, T, C = x.size()
+        nh, hs  = self.num_heads, self.head_dim
+        q, k, v = self.c_attn(x).split(C, dim=2)
+        q = q.view(B, T, nh, hs).transpose(1, 2)   # (B, nh, T, hs)
+        k = k.view(B, T, nh, hs).transpose(1, 2)
+        v = v.view(B, T, nh, hs).transpose(1, 2)
+
+        # Use PyTorch SDPA — this is what vLLM hooks into
+        # is_causal=True handles the causal mask automatically
+        y = F.scaled_dot_product_attention(
+            q, k, v,
+            attn_mask=None,
+            dropout_p=self.attn_drop if self.training else 0.0,
+            is_causal=True,
+        )
+        y = y.transpose(1, 2).contiguous().view(B, T, C)
+        return self.resid_drop(self.c_proj(y))
+
+
+class EasySellMLP(nn.Module):
+    def __init__(self, config: EasySellConfig):
+        super().__init__()
+        self.fc      = nn.Linear(config.hidden_size, 4 * config.hidden_size)
+        self.proj    = nn.Linear(4 * config.hidden_size, config.hidden_size)
+        self.dropout = nn.Dropout(config.hidden_dropout_prob)
+
+    def forward(self, x):
+        return self.dropout(self.proj(F.gelu(self.fc(x))))
+
+
+class EasySellBlock(nn.Module):
+    def __init__(self, config: EasySellConfig):
+        super().__init__()
+        self.ln1  = nn.LayerNorm(config.hidden_size)
+        self.attn = EasySellAttention(config)
+        self.ln2  = nn.LayerNorm(config.hidden_size)
+        self.mlp  = EasySellMLP(config)
+
+    def forward(self, x, attention_mask=None):
+        x = x + self.attn(self.ln1(x), attention_mask)
+        x = x + self.mlp(self.ln2(x))
+        return x
+
+
+class EasySellModel(nn.Module):
+    """Core transformer backbone (no LM head)."""
+
+    def __init__(self, config: EasySellConfig):
+        super().__init__()
+        self.wte    = nn.Embedding(config.vocab_size, config.hidden_size)
+        self.wpe    = nn.Embedding(config.max_position_embeddings, config.hidden_size)
+        self.drop   = nn.Dropout(config.hidden_dropout_prob)
+        self.blocks = nn.ModuleList([EasySellBlock(config) for _ in range(config.num_hidden_layers)])
+        self.ln_f   = nn.LayerNorm(config.hidden_size)
+
+    def forward(self, input_ids, attention_mask=None):
+        B, T = input_ids.size()
+        pos  = torch.arange(T, device=input_ids.device).unsqueeze(0)
+        x    = self.drop(self.wte(input_ids) + self.wpe(pos))
+        for block in self.blocks:
+            x = block(x, attention_mask)
+        return self.ln_f(x)
+
+
+class EasySellForCausalLM(PreTrainedModel, GenerationMixin):
+    """
+    EasySell AI — HuggingFace + vLLM compatible causal LM.
+    Load with: AutoModelForCausalLM.from_pretrained(..., trust_remote_code=True)
+    """
+    config_class          = EasySellConfig
+    base_model_prefix     = "model"
+    supports_gradient_checkpointing = False
+
+    def __init__(self, config: EasySellConfig):
+        super().__init__(config)
+        self.model   = EasySellModel(config)
+        self.lm_head = nn.Linear(config.hidden_size, config.vocab_size, bias=False)
+        self.post_init()
+
+    def get_input_embeddings(self):
+        return self.model.wte
+
+    def set_input_embeddings(self, value):
+        self.model.wte = value
+
+    def get_output_embeddings(self):
+        return self.lm_head
+
+    def set_output_embeddings(self, new_embeddings):
+        self.lm_head = new_embeddings
+
+    def forward(
+        self,
+        input_ids=None,
+        attention_mask=None,
+        labels=None,
+        **kwargs,
+    ):
+        hidden = self.model(input_ids, attention_mask=attention_mask)
+        logits = self.lm_head(hidden)
+
+        loss = None
+        if labels is not None:
+            loss = F.cross_entropy(
+                logits.view(-1, logits.size(-1)),
+                labels.view(-1),
+                ignore_index=-100,
+            )
+
+        return CausalLMOutputWithPast(
+            loss=loss,
+            logits=logits,
+            past_key_values=None,
+            hidden_states=None,
+            attentions=None,
+        )
+
+    def prepare_inputs_for_generation(self, input_ids, **kwargs):
+        """Required by HF .generate() and vLLM."""
+        return {"input_ids": input_ids}
+
+    @torch.no_grad()
+    def generate_tool_call(
+        self,
+        input_ids,
+        max_new_tokens=120,
+        temperature=0.1,
+        top_k=30,
+        eos_token_id=2,
+    ):
+        """Convenience greedy sampler — same logic as original training notebook."""
+        self.eval()
+        x = input_ids.to(next(self.parameters()).device)
+        generated = []
+        for _ in range(max_new_tokens):
+            x_cond = x[:, -self.config.max_position_embeddings:]
+            logits = self.forward(x_cond).logits[:, -1, :] / max(temperature, 1e-6)
+            if top_k > 0:
+                v, ix = torch.topk(logits, top_k)
+                probs = torch.zeros_like(logits).scatter_(1, ix, F.softmax(v, dim=-1))
+            else:
+                probs = F.softmax(logits, dim=-1)
+            next_id = torch.multinomial(probs, num_samples=1)
+            if next_id.item() == eos_token_id:
+                break
+            generated.append(next_id.item())
+            if len(generated) >= 8 and len(set(generated[-8:])) <= 2:
+                break
+            x = torch.cat([x, next_id], dim=1)
+        return generated

tokenizer.json

@@ -0,0 +1,4070 @@
+{
+  "version": "1.0",
+  "truncation": null,
+  "padding": null,
+  "added_tokens": [
+    {
+      "id": 0,
+      "content": "[PAD]",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    {
+      "id": 1,
+      "content": "[BOS]",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    {
+      "id": 2,
+      "content": "[EOS]",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    {
+      "id": 3,
+      "content": "[UNK]",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    }
+  ],
+  "normalizer": null,
+  "pre_tokenizer": {
+    "type": "Whitespace"
+  },
+  "post_processor": null,
+  "decoder": {
+    "type": "BPEDecoder",
+    "suffix": "</w>"
+  },
+  "model": {
+    "type": "BPE",
+    "dropout": null,
+    "unk_token": "[UNK]",
+    "continuing_subword_prefix": null,
+    "end_of_word_suffix": null,
+    "fuse_unk": false,
+    "byte_fallback": false,
+    "ignore_merges": false,
+    "vocab": {
+      "[PAD]": 0,
+      "[BOS]": 1,
+      "[EOS]": 2,
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+        "b",
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+        "w",
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+        "b",
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+        "bang",
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+        "s",
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+        "c",
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+        "po",
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+        "f",
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+        "bangle",
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+        "wat",
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+        "s",
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+        "un",
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+      [
+        "scr",
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+        "b",
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+      ],
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+        "t",
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+      [
+        "bot",
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+      ],
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+        "i",
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+      ],
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+        "a",
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+      [
+        "p",
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+      [
+        "h",
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+      ],
+      [
+        "di",
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+      ],
+      [
+        "ah",
+        "i"
+      ],
+      [
+        "car",
+        "s"
+      ],
+      [
+        "or",
+        "al"
+      ],
+      [
+        "fl",
+        "oral"
+      ],
+      [
+        "re",
+        "d"
+      ],
+      [
+        "poco",
+        "toy"
+      ],
+      [
+        "an",
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+      ],
+      [
+        "st",
+        "anle"
+      ],
+      [
+        "stanle",
+        "y"
+      ],
+      [
+        "b",
+        "oo"
+      ],
+      [
+        "boo",
+        "ks"
+      ],
+      [
+        "la",
+        "p"
+      ],
+      [
+        "ring",
+        "s"
+      ],
+      [
+        "mo",
+        "b"
+      ],
+      [
+        "to",
+        "p"
+      ],
+      [
+        "sheet",
+        "s"
+      ],
+      [
+        "k",
+        "ar"
+      ],
+      [
+        "a",
+        "w"
+      ],
+      [
+        "sh",
+        "aw"
+      ],
+      [
+        "shaw",
+        "l"
+      ],
+      [
+        "y",
+        "e"
+      ],
+      [
+        "ch",
+        "ahi"
+      ],
+      [
+        "chahi",
+        "ye"
+      ],
+      [
+        "scrunch",
+        "ies"
+      ],
+      [
+        "lap",
+        "top"
+      ],
+      [
+        "hoo",
+        "die"
+      ],
+      [
+        "i",
+        "le"
+      ],
+      [
+        "mob",
+        "ile"
+      ],
+      [
+        "i",
+        "um"
+      ],
+      [
+        "m",
+        "ium"
+      ],
+      [
+        "p",
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+      ],
+      [
+        "pre",
+        "mium"
+      ],
+      [
+        "b",
+        "o"
+      ],
+      [
+        "bo",
+        "ok"
+      ],
+      [
+        "i",
+        "e"
+      ],
+      [
+        "kar",
+        "o"
+      ],
+      [
+        "s",
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+      ],
+      [
+        "sen",
+        "d"
+      ],
+      [
+        "h",
+        "ai"
+      ],
+      [
+        "O",
+        "R"
+      ],
+      [
+        "OR",
+        "D"
+      ],
+      [
+        "l",
+        "l"
+      ],
+      [
+        "hai",
+        "r"
+      ],
+      [
+        "e",
+        "ed"
+      ],
+      [
+        "n",
+        "eed"
+      ],
+      [
+        "h",
+        "o"
+      ],
+      [
+        "h",
+        "one"
+      ],
+      [
+        "p",
+        "hone"
+      ],
+      [
+        "m",
+        "art"
+      ],
+      [
+        "s",
+        "mart"
+      ],
+      [
+        "l",
+        "d"
+      ],
+      [
+        "p",
+        "ie"
+      ],
+      [
+        "pie",
+        "ce"
+      ],
+      [
+        "g",
+        "h"
+      ],
+      [
+        "d",
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+      ],
+      [
+        "don",
+        "t"
+      ],
+      [
+        "4",
+        "2"
+      ],
+      [
+        "k",
+        "i"
+      ],
+      [
+        "l",
+        "ad"
+      ],
+      [
+        "lad",
+        "ies"
+      ],
+      [
+        "1",
+        "2"
+      ],
+      [
+        "p",
+        "le"
+      ],
+      [
+        "ple",
+        "ase"
+      ],
+      [
+        "i",
+        "ve"
+      ],
+      [
+        "at",
+        "a"
+      ],
+      [
+        "hoo",
+        "d"
+      ],
+      [
+        "p",
+        "r"
+      ],
+      [
+        "ic",
+        "e"
+      ],
+      [
+        "pr",
+        "ice"
+      ],
+      [
+        "g",
+        "ive"
+      ],
+      [
+        "\"",
+        "#"
+      ],
+      [
+        "n",
+        "ahi"
+      ],
+      [
+        "w",
+        "ou"
+      ],
+      [
+        "li",
+        "ke"
+      ],
+      [
+        "wou",
+        "ld"
+      ],
+      [
+        "j",
+        "he"
+      ],
+      [
+        "m",
+        "u"
+      ],
+      [
+        "change",
+        "d"
+      ],
+      [
+        "mu",
+        "jhe"
+      ],
+      [
+        "i",
+        "gh"
+      ],
+      [
+        "r",
+        "igh"
+      ],
+      [
+        "righ",
+        "t"
+      ],
+      [
+        "m",
+        "ake"
+      ],
+      [
+        "piece",
+        "s"
+      ],
+      [
+        "t",
+        "er"
+      ],
+      [
+        "te",
+        "d"
+      ],
+      [
+        "in",
+        "ter"
+      ],
+      [
+        "es",
+        "ted"
+      ],
+      [
+        "inter",
+        "ested"
+      ],
+      [
+        "look",
+        "ing"
+      ],
+      [
+        "n",
+        "i"
+      ],
+      [
+        "ch",
+        "un"
+      ],
+      [
+        "chun",
+        "ni"
+      ],
+      [
+        "sto",
+        "le"
+      ],
+      [
+        "m",
+        "ind"
+      ],
+      [
+        "a",
+        "p"
+      ],
+      [
+        "r",
+        "ap"
+      ],
+      [
+        "w",
+        "rap"
+      ],
+      [
+        "p",
+        "at"
+      ],
+      [
+        "t",
+        "a"
+      ],
+      [
+        "du",
+        "pat"
+      ],
+      [
+        "dupat",
+        "ta"
+      ],
+      [
+        "y",
+        "o"
+      ],
+      [
+        "poco",
+        "yo"
+      ],
+      [
+        "s",
+        "te"
+      ],
+      [
+        "in",
+        "ste"
+      ],
+      [
+        "inste",
+        "ad"
+      ],
+      [
+        "0",
+        "8"
+      ],
+      [
+        "3",
+        "08"
+      ],
+      [
+        "308",
+        "9"
+      ],
+      [
+        "0",
+        "42"
+      ],
+      [
+        "2",
+        "042"
+      ],
+      [
+        "k",
+        "ha"
+      ],
+      [
+        "di",
+        "kha"
+      ],
+      [
+        "dikha",
+        "o"
+      ],
+      [
+        "k",
+        "a"
+      ],
+      [
+        "fro",
+        "ck"
+      ],
+      [
+        "3",
+        "4"
+      ],
+      [
+        "12",
+        "34"
+      ],
+      [
+        "as",
+        "k"
+      ],
+      [
+        "fl",
+        "ask"
+      ],
+      [
+        "lap",
+        "y"
+      ],
+      [
+        "scrunch",
+        "ie"
+      ],
+      [
+        "0",
+        "0"
+      ],
+      [
+        "1",
+        "00"
+      ],
+      [
+        "100",
+        "1"
+      ],
+      [
+        "b",
+        "ata"
+      ],
+      [
+        "bata",
+        "o"
+      ],
+      [
+        "pp",
+        "y"
+      ],
+      [
+        "po",
+        "p"
+      ],
+      [
+        "la",
+        "ppy"
+      ],
+      [
+        "la",
+        "pop"
+      ],
+      [
+        "f",
+        "ing"
+      ],
+      [
+        "fing",
+        "er"
+      ],
+      [
+        "ad",
+        "ar"
+      ],
+      [
+        "ch",
+        "adar"
+      ],
+      [
+        "t",
+        "ie"
+      ],
+      [
+        "g",
+        "al"
+      ],
+      [
+        "i",
+        "me"
+      ],
+      [
+        "t",
+        "ime"
+      ],
+      [
+        "an",
+        "alog"
+      ],
+      [
+        "time",
+        "piece"
+      ],
+      [
+        "put",
+        "er"
+      ],
+      [
+        "com",
+        "puter"
+      ],
+      [
+        "e",
+        "at"
+      ],
+      [
+        "s",
+        "w"
+      ],
+      [
+        "eat",
+        "shirt"
+      ],
+      [
+        "sw",
+        "eatshirt"
+      ],
+      [
+        "i",
+        "pp"
+      ],
+      [
+        "s",
+        "ipp"
+      ],
+      [
+        "sipp",
+        "er"
+      ],
+      [
+        "n",
+        "o"
+      ],
+      [
+        "s",
+        "am"
+      ],
+      [
+        "s",
+        "un"
+      ],
+      [
+        "te",
+        "book"
+      ],
+      [
+        "no",
+        "tebook"
+      ],
+      [
+        "sam",
+        "sun"
+      ],
+      [
+        "samsun",
+        "g"
+      ],
+      [
+        "b",
+        "e"
+      ],
+      [
+        "b",
+        "and"
+      ],
+      [
+        "dd",
+        "ing"
+      ],
+      [
+        "be",
+        "dding"
+      ],
+      [
+        "r",
+        "y"
+      ],
+      [
+        "sto",
+        "ry"
+      ],
+      [
+        "a",
+        "st"
+      ],
+      [
+        "u",
+        "di"
+      ],
+      [
+        "ch",
+        "udi"
+      ],
+      [
+        "el",
+        "ast"
+      ],
+      [
+        "elast",
+        "ic"
+      ],
+      [
+        "wat",
+        "er"
+      ],
+      [
+        "scrunch",
+        "y"
+      ],
+      [
+        "a",
+        "ch"
+      ],
+      [
+        "w",
+        "ach"
+      ],
+      [
+        "c",
+        "ol"
+      ],
+      [
+        "j",
+        "o"
+      ],
+      [
+        "le",
+        "ge"
+      ],
+      [
+        "ho",
+        "die"
+      ],
+      [
+        "smart",
+        "phone"
+      ],
+      [
+        "col",
+        "lege"
+      ],
+      [
+        "bag",
+        "pack"
+      ],
+      [
+        "te",
+        "ll"
+      ],
+      [
+        "ad",
+        "i"
+      ],
+      [
+        "gh",
+        "adi"
+      ],
+      [
+        "b",
+        "ack"
+      ],
+      [
+        "back",
+        "pack"
+      ],
+      [
+        "c",
+        "as"
+      ],
+      [
+        "i",
+        "phone"
+      ],
+      [
+        "i",
+        "ld"
+      ],
+      [
+        "u",
+        "al"
+      ],
+      [
+        "ch",
+        "ild"
+      ],
+      [
+        "cas",
+        "ual"
+      ],
+      [
+        "child",
+        "ren"
+      ],
+      [
+        "o",
+        "ol"
+      ],
+      [
+        "s",
+        "ch"
+      ],
+      [
+        "t",
+        "shirt"
+      ],
+      [
+        "women",
+        "s"
+      ],
+      [
+        "sch",
+        "ool"
+      ],
+      [
+        "hood",
+        "y"
+      ],
+      [
+        "r",
+        "u"
+      ],
+      [
+        "s",
+        "ack"
+      ],
+      [
+        "ck",
+        "sack"
+      ],
+      [
+        "ru",
+        "cksack"
+      ],
+      [
+        "sh",
+        "are"
+      ],
+      [
+        "dd",
+        "y"
+      ],
+      [
+        "ho",
+        "ddy"
+      ],
+      [
+        "m",
+        "al"
+      ],
+      [
+        "for",
+        "mal"
+      ],
+      [
+        "d",
+        "die"
+      ],
+      [
+        "ho",
+        "ddie"
+      ],
+      [
+        "1",
+        "8"
+      ],
+      [
+        "U",
+        "P"
+      ],
+      [
+        "c",
+        "to"
+      ],
+      [
+        "id",
+        "a"
+      ],
+      [
+        "No",
+        "ida"
+      ],
+      [
+        "Se",
+        "cto"
+      ],
+      [
+        "Secto",
+        "r"
+      ],
+      [
+        "j",
+        "ust"
+      ],
+      [
+        "smart",
+        "watch"
+      ],
+      [
+        "B",
+        "en"
+      ],
+      [
+        "M",
+        "G"
+      ],
+      [
+        "R",
+        "o"
+      ],
+      [
+        "ur",
+        "u"
+      ],
+      [
+        "gal",
+        "uru"
+      ],
+      [
+        "Ben",
+        "galuru"
+      ],
+      [
+        "Ro",
+        "ad"
+      ],
+      [
+        "c",
+        "li"
+      ],
+      [
+        "cli",
+        "ck"
+      ],
+      [
+        "b",
+        "he"
+      ],
+      [
+        "bhe",
+        "jo"
+      ],
+      [
+        "K",
+        "ol"
+      ],
+      [
+        "P",
+        "ar"
+      ],
+      [
+        "S",
+        "t"
+      ],
+      [
+        "k",
+        "ang"
+      ],
+      [
+        "k",
+        "ata"
+      ],
+      [
+        "re",
+        "et"
+      ],
+      [
+        "Kol",
+        "kata"
+      ],
+      [
+        "Par",
+        "k"
+      ],
+      [
+        "St",
+        "reet"
+      ],
+      [
+        "kang",
+        "an"
+      ],
+      [
+        "cel",
+        "l"
+      ],
+      [
+        "bed",
+        "sheet"
+      ],
+      [
+        "A",
+        "n"
+      ],
+      [
+        "F",
+        "l"
+      ],
+      [
+        "M",
+        "umb"
+      ],
+      [
+        "d",
+        "h"
+      ],
+      [
+        "er",
+        "i"
+      ],
+      [
+        "An",
+        "dh"
+      ],
+      [
+        "Fl",
+        "at"
+      ],
+      [
+        "Mumb",
+        "ai"
+      ],
+      [
+        "Andh",
+        "eri"
+      ],
+      [
+        "i",
+        "ck"
+      ],
+      [
+        "qu",
+        "ick"
+      ],
+      [
+        "5",
+        "6"
+      ],
+      [
+        "7",
+        "8"
+      ],
+      [
+        "e",
+        "very"
+      ],
+      [
+        "t",
+        "hing"
+      ],
+      [
+        "56",
+        "78"
+      ],
+      [
+        "every",
+        "thing"
+      ],
+      [
+        "n",
+        "g"
+      ],
+      [
+        "w",
+        "ro"
+      ],
+      [
+        "wro",
+        "ng"
+      ],
+      [
+        "w",
+        "i"
+      ],
+      [
+        "k",
+        "y"
+      ],
+      [
+        "ky",
+        "a"
+      ],
+      [
+        "n",
+        "a"
+      ],
+      [
+        "kar",
+        "na"
+      ],
+      [
+        "hat",
+        "a"
+      ],
+      [
+        "pro",
+        "ce"
+      ],
+      [
+        "proce",
+        "ed"
+      ],
+      [
+        "g",
+        "enerate"
+      ],
+      [
+        "what",
+        "s"
+      ],
+      [
+        "add",
+        "ed"
+      ],
+      [
+        "h",
+        "og"
+      ],
+      [
+        "k",
+        "ab"
+      ],
+      [
+        "move",
+        "d"
+      ],
+      [
+        "gal",
+        "at"
+      ],
+      [
+        "hog",
+        "i"
+      ],
+      [
+        "k",
+        "ah"
+      ],
+      [
+        "k",
+        "ho"
+      ],
+      [
+        "mer",
+        "a"
+      ],
+      [
+        "de",
+        "kho"
+      ],
+      [
+        "oo",
+        "s"
+      ],
+      [
+        "kah",
+        "an"
+      ],
+      [
+        "r",
+        "ive"
+      ],
+      [
+        "ar",
+        "rive"
+      ],
+      [
+        "wi",
+        "ll"
+      ],
+      [
+        "h",
+        "as"
+      ],
+      [
+        "p",
+        "ped"
+      ],
+      [
+        "shi",
+        "pped"
+      ],
+      [
+        "pack",
+        "age"
+      ],
+      [
+        "wi",
+        "pe"
+      ],
+      [
+        "s",
+        "ab"
+      ],
+      [
+        "se",
+        "ll"
+      ],
+      [
+        "o",
+        "h"
+      ],
+      [
+        "w",
+        "oh"
+      ],
+      [
+        "me",
+        "in"
+      ],
+      [
+        "f",
+        "re"
+      ],
+      [
+        "fre",
+        "sh"
+      ]
+    ]
+  }
+}

tokenizer_config.json

@@ -0,0 +1,7 @@
+{
+  "tokenizer_class": "PreTrainedTokenizerFast",
+  "bos_token": "[BOS]",
+  "eos_token": "[EOS]",
+  "pad_token": "[PAD]",
+  "model_max_length": 1024
+}