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Model: prithivMLmods/Llama-SmolTalk-3.2-1B-Instruct Source: Original Platform
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README.md
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README.md
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---
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license: creativeml-openrail-m
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datasets:
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- HuggingFaceTB/smoltalk
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language:
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- en
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base_model:
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- meta-llama/Llama-3.2-1B-Instruct
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pipeline_tag: text-generation
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library_name: transformers
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tags:
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- Llama
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- Llama-CPP
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- SmolTalk
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- ollama
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- bin
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---
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## Llama-SmolTalk-3.2-1B-Instruct Model File
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The **Llama-SmolTalk-3.2-1B-Instruct** model is a lightweight, instruction-tuned model designed for efficient text generation and conversational AI tasks. With a 1B parameter architecture, this model strikes a balance between performance and resource efficiency, making it ideal for applications requiring concise, contextually relevant outputs. The model has been fine-tuned to deliver robust instruction-following capabilities, catering to both structured and open-ended queries.
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| File Name [ Updated Files ] | Size | Description | Upload Status |
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|----------------------------|-----------|--------------------------------------------|----------------|
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| `.gitattributes` | 1.57 kB | Git attributes configuration file | Uploaded |
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| `README.md` | 42 Bytes | Initial README | Uploaded |
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| `config.json` | 1.03 kB | Configuration file | Uploaded |
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| `generation_config.json` | 248 Bytes | Configuration for text generation | Uploaded |
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| `pytorch_model.bin` | 2.47 GB | PyTorch model weights | Uploaded (LFS) |
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| `special_tokens_map.json` | 477 Bytes | Special token mappings | Uploaded |
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| `tokenizer.json` | 17.2 MB | Tokenizer configuration | Uploaded (LFS) |
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| `tokenizer_config.json` | 57.4 kB | Additional tokenizer settings | Uploaded |
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| Model Type | Size | Context Length | Link |
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|------------|------|----------------|------|
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| GGUF | 1B | - | [🤗 Llama-SmolTalk-3.2-1B-Instruct-GGUF](https://huggingface.co/prithivMLmods/Llama-SmolTalk-3.2-1B-Instruct-GGUF) |
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### Key Features:
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1. **Instruction-Tuned Performance**: Optimized to understand and execute user-provided instructions across diverse domains.
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2. **Lightweight Architecture**: With just 1 billion parameters, the model provides efficient computation and storage without compromising output quality.
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3. **Versatile Use Cases**: Suitable for tasks like content generation, conversational interfaces, and basic problem-solving.
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### Intended Applications:
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- **Conversational AI**: Engage users with dynamic and contextually aware dialogue.
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- **Content Generation**: Produce summaries, explanations, or other creative text outputs efficiently.
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- **Instruction Execution**: Follow user commands to generate precise and relevant responses.
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### Technical Details:
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The model leverages PyTorch for training and inference, with a tokenizer optimized for seamless text input processing. It comes with essential configuration files, including `config.json`, `generation_config.json`, and tokenization files (`tokenizer.json` and `special_tokens_map.json`). The primary weights are stored in a PyTorch binary format (`pytorch_model.bin`), ensuring easy integration with existing workflows.
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**Model Type**: GGUF
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**Size**: 1B Parameters
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The **Llama-SmolTalk-3.2-1B-Instruct** model is an excellent choice for lightweight text generation tasks, offering a blend of efficiency and effectiveness for a wide range of applications.
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config.json
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config.json
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{
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"_name_or_path": "unsloth/llama-3.2-1b-instruct-bnb-4bit",
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"architectures": [
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"LlamaForCausalLM"
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],
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"attention_bias": false,
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"attention_dropout": 0.0,
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"bos_token_id": 128000,
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"eos_token_id": [
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128001,
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128008,
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128009
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],
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"head_dim": 64,
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"hidden_act": "silu",
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"hidden_size": 2048,
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"initializer_range": 0.02,
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"intermediate_size": 8192,
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"max_position_embeddings": 131072,
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"mlp_bias": false,
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"model_type": "llama",
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"num_attention_heads": 32,
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"num_hidden_layers": 16,
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"num_key_value_heads": 8,
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"pad_token_id": 128004,
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"pretraining_tp": 1,
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"rms_norm_eps": 1e-05,
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"rope_scaling": {
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"factor": 32.0,
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"high_freq_factor": 4.0,
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"low_freq_factor": 1.0,
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"original_max_position_embeddings": 8192,
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"rope_type": "llama3"
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},
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"rope_theta": 500000.0,
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"tie_word_embeddings": true,
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"torch_dtype": "float16",
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"transformers_version": "4.46.2",
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"unsloth_version": "2024.11.9",
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"use_cache": true,
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"vocab_size": 128256
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}
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configuration.json
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configuration.json
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{"framework": "pytorch", "task": "text-generation", "allow_remote": true}
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generation_config.json
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generation_config.json
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{
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"bos_token_id": 128000,
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"do_sample": true,
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"eos_token_id": [
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128001,
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128008,
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128009
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],
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"max_length": 131072,
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"pad_token_id": 128004,
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"temperature": 0.6,
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"top_p": 0.9,
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"transformers_version": "4.46.2"
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}
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:3cb2675115984e8d4c24394de76b91f7b5c40b070cb3ec07aa091de69cbc3d1d
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size 2471645464
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special_tokens_map.json
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{
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"bos_token": {
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"content": "<|begin_of_text|>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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},
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"eos_token": {
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"content": "<|eot_id|>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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},
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"pad_token": {
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"content": "<|finetune_right_pad_id|>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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}
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}
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BIN
tokenizer.json
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tokenizer.json
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2064
tokenizer_config.json
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tokenizer_config.json
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