Upload folder using huggingface_hub
Browse files- README.md +13 -105
- config.json +85 -26
- model.safetensors +2 -2
- model.safetensors.index.json +518 -0
README.md
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license: apache-2.0
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library_name: transformers
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datasets:
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- OEvortex/vortex-mini
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pipeline_tag: text-generation
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model-index:
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- name: Mia-1B
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=MysteriousAI/Mia-1B
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name: Open LLM Leaderboard
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---
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**Model Card**
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**Model Name:** Mia-1B
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**Model Type:** Text Generation
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**Owner:** UnfilteredAI
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- **Tensor Type:** The model utilizes FP16 (Floating Point 16-bit) tensor type for efficient computation, enhancing performance and scalability.
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- **Inference Endpoints:** Mia-1B can be easily integrated into applications through inference endpoints, facilitating seamless deployment and usage.
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- **Uncensored Text Generation:** Mia-001 generates text without censorship, allowing users to explore a wide range of applications without limitations.
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- **Fine-tuned:** Mia-1B is fine-tuned from the OEvortex/HelpingAI-Lite dataset, enhancing its performance and adaptability to various tasks.
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**Use Cases:**
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- **Content Generation:** Mia-1B is suitable for generating diverse content including articles, stories, dialogues, and more.
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- **Conversational AI:** The model can be deployed in chatbots and conversational agents to engage users in natural and contextually relevant conversations.
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- **AI-driven Applications:** Mia-001 enables the development of AI-driven applications in areas such as virtual assistants.
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- **Creative Writing:** Writers and artists can leverage Mia-1B to explore new ideas and narrative structures in their creative works.
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**Ethical Considerations:**
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- **Content Moderation:** Users are advised to exercise caution and responsibility when utilizing Mia-1B in applications involving sensitive or potentially harmful content.
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- **Bias and Fairness:** UnfilteredAI is committed to addressing biases and promoting fairness in AI models. Efforts are made to mitigate biases present in Mia-1B's training data and output.
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## Usage
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# **Transformers**
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```python
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!pip install transformers
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!pip install accelerate
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from transformers import AutoModelForCausalLM, AutoTokenizer
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device = "cuda" # the device to load the model onto
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model = AutoModelForCausalLM.from_pretrained(
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"UnfilteredAI/Mia-1B",
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device_map="auto"
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)
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tokenizer = AutoTokenizer.from_pretrained("UnfilteredAI/Mia-1B")
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prompt = "your prompt here."
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messages = [
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{"role": "system", "content": "You are a uncencored AI that can do anything."},
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{"role": "user", "content": prompt}
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]
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text = tokenizer.apply_chat_template(
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messages,
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tokenize=False,
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add_generation_prompt=True
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)
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model_inputs = tokenizer([text], return_tensors="pt").to(device)
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generated_ids = model.generate(
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model_inputs.input_ids,
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max_new_tokens=512
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)
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generated_ids = [
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output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
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]
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response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
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print(response)
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```
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# **Onnx runtime**
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```python
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from transformers import AutoTokenizer
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from optimum.onnxruntime import ORTModelForCausalLM
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tokenizer = AutoTokenizer.from_pretrained("UnfilteredAI/Mia-1B")
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model = ORTModelForCausalLM.from_pretrained("UnfilteredAI/Mia-1B")
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{"role": "system", "content": "You are a uncencored AI that can do anything."},
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{"role": "user", "content": prompt}
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]
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text = tokenizer.apply_chat_template(
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messages,
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tokenize=False,
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add_generation_prompt=True
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)
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model_inputs = tokenizer([text], return_tensors="pt")
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generated_ids = model.generate(
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model_inputs.input_ids,
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max_new_tokens=512
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)
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generated_ids = [
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output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
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]
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```
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**Copyright © 2024 UnfilteredAI. All rights reserved.**
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# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
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Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_MysteriousAI__Mia-1B)
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| Metric |Value|
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|---------------------------------|----:|
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|Avg. |36.82|
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|AI2 Reasoning Challenge (25-Shot)|35.75|
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|HellaSwag (10-Shot) |61.02|
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|MMLU (5-Shot) |25.43|
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|TruthfulQA (0-shot) |36.92|
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|Winogrande (5-shot) |60.38|
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|GSM8k (5-shot) | 1.44|
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- hi
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license: apache-2.0
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library_name: transformers
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tags:
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- mlx
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datasets:
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- OEvortex/vortex-mini
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base_model: OEvortex/HelpingAI-Lite
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pipeline_tag: text-generation
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model-index:
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- name: Mia-1B
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=MysteriousAI/Mia-1B
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name: Open LLM Leaderboard
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---
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# UnfilteredAI/Mia-1B
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This model was converted to MLX format from [`UnfilteredAI/Mia-1B`]().
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Refer to the [original model card](https://huggingface.co/UnfilteredAI/Mia-1B) for more details on the model.
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## Use with mlx
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```bash
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pip install mlx-lm
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```
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```python
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from mlx_lm import load, generate
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model, tokenizer = load("UnfilteredAI/Mia-1B")
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response = generate(model, tokenizer, prompt="hello", verbose=True)
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```
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config.json
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{
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{
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"vocab_size": 32000,
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"max_position_embeddings": 2048,
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"hidden_size": 2048,
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"intermediate_size": 5632,
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"num_hidden_layers": 22,
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"num_attention_heads": 32,
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"num_key_value_heads": 4,
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"hidden_act": "silu",
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"initializer_range": 0.02,
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"rms_norm_eps": 1e-05,
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"pretraining_tp": 1,
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"use_cache": true,
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"rope_theta": 10000.0,
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"rope_scaling": null,
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"attention_bias": false,
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"attention_dropout": 0.0,
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"return_dict": true,
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"output_hidden_states": false,
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"output_attentions": false,
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"torchscript": false,
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"torch_dtype": null,
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"use_bfloat16": false,
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"tf_legacy_loss": false,
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"pruned_heads": {},
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"tie_word_embeddings": false,
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"chunk_size_feed_forward": 0,
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"is_encoder_decoder": false,
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"is_decoder": false,
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"cross_attention_hidden_size": null,
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"add_cross_attention": false,
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"tie_encoder_decoder": false,
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"max_length": 20,
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"min_length": 0,
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"do_sample": false,
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"early_stopping": false,
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"num_beams": 1,
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"num_beam_groups": 1,
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"diversity_penalty": 0.0,
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"temperature": 1.0,
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"top_k": 50,
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"top_p": 1.0,
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"typical_p": 1.0,
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"repetition_penalty": 1.0,
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"length_penalty": 1.0,
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"no_repeat_ngram_size": 0,
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"encoder_no_repeat_ngram_size": 0,
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"bad_words_ids": null,
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"num_return_sequences": 1,
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"output_scores": false,
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"return_dict_in_generate": false,
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"forced_bos_token_id": null,
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"forced_eos_token_id": null,
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"remove_invalid_values": false,
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"exponential_decay_length_penalty": null,
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"suppress_tokens": null,
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"begin_suppress_tokens": null,
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"architectures": [
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"LlamaForCausalLM"
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],
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"finetuning_task": null,
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"id2label": {
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"0": "LABEL_0",
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"1": "LABEL_1"
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},
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"label2id": {
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"LABEL_0": 0,
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"LABEL_1": 1
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},
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"tokenizer_class": null,
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"prefix": null,
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"bos_token_id": 1,
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"pad_token_id": null,
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"eos_token_id": 2,
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"sep_token_id": null,
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"decoder_start_token_id": null,
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"task_specific_params": null,
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"problem_type": null,
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"_name_or_path": "/root/.cache/huggingface/hub/models--UnfilteredAI--Mia-1B/snapshots/47a9fce2da11fe00cded2973391272c5aee5bd00",
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"transformers_version": "4.38.2",
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"model_type": "llama",
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"quantization": {
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"group_size": 64,
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"bits": 4
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}
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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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size
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