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Model: KumarXAI/BiniGPT-0.1B-FM
Source: Original Platform

.gitattributes

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README.md

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+---
+library_name: transformers
+license: mit
+language:
+- en
+base_model:
+- openai-community/gpt2
+tags:
+- BiniGPT
+---
+
+### Model Description
+Welcome to *BiniGPT-0.1B-FM*! This is my very first model upload to Hugging Face. 
+
+I am uploading this to establish my deployment pipeline and lay the groundwork for my future custom model series. This repository hosts weight configurations originating from the open-source GPT-2 model series developed and released by OpenAI. All credit for the baseline architecture and primary pretraining goes to the original authors. The model is distributed under the permissive MIT License.
+
+- **Model name:** BiniGPT-0.1B-FM
+- **Model type:** Causal Language Model (Transformer Decoder)
+- **Base model:** GPT 2
+- **Language(s) (NLP):** English
+- **License:** MIT
+- **Shared by:** Abhishek Kumar (KumarXAI)
+
+### Direct Use
+This model is best used to test inference performance, validate local pipeline architectures, or experiment with few-shot prompting templates to direct next-token behavior.
+
+**Quickstart: Run in 30 Seconds**
+
+Ensure you have transformers and torch installed, then run the snippet below:
+```bash
+pip install transformers torch
+```
+1. Using the Pipeline (High-Level Helper)
+You can test the model easily using Hugging Face's high-level pipeline helper. This automatically handles downloading the weights, setting up the tokenizer, and generating text:
+```python
+from transformers import pipeline
+
+# Use a pipeline as a high-level helper
+pipe = pipeline("text-generation", model="KumarXAI/BiniGPT-0.1B-FM")
+
+# Run inference on a prompt
+prompt = "The secret of scientific discovery is"
+outputs = pipe(prompt, max_new_tokens=25, do_sample=True, temperature=0.7)
+print(outputs[0]["generated_text"])
+```
+
+2. Loading Model and Tokenizer Directly
+If you need to interact directly with the model's inner workings (the building blocks of AI) to customize generation parameters:
+
+```python
+import torch
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+# Load model directly
+tokenizer = AutoTokenizer.from_pretrained("KumarXAI/BiniGPT-0.1B-FM")
+model = AutoModelForCausalLM.from_pretrained("KumarXAI/BiniGPT-0.1B-FM")
+
+# Setup input
+prompt = "In the heart of Mithila, a great scholar discovered"
+inputs = tokenizer(prompt, return_tensors="pt")
+
+# Generate with custom settings
+output_ids = model.generate(
+    **inputs,
+    max_new_tokens=50,
+    do_sample=True,
+    temperature=0.8,
+    top_p=0.95,
+    pad_token_id=tokenizer.eos_token_id
+)
+
+print(tokenizer.decode(output_ids[0], skip_special_tokens=True))
+```
+
+### Out-of-Scope Use
+- **No Safety Alignment:** Because this is a raw base model, it has not undergone RLHF (Reinforcement Learning from Human Feedback) or safety instruction tuning.
+- **Not a Conversational Model:** It will naturally seek to complete text blocks rather than answer questions like an assistant.
+- **Hallucinations:** The model is highly prone to factual errors, generating biased language, and repeating phrases. Do not rely on it for critical factual retrieval.
+
+
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]

config.json

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+{
+  "activation_function": "gelu_new",
+  "add_cross_attention": false,
+  "architectures": [
+    "GPT2LMHeadModel"
+  ],
+  "attn_pdrop": 0.1,
+  "bos_token_id": 50256,
+  "dtype": "float32",
+  "embd_pdrop": 0.1,
+  "eos_token_id": 50256,
+  "initializer_range": 0.02,
+  "layer_norm_epsilon": 1e-05,
+  "model_type": "gpt2",
+  "n_ctx": 1024,
+  "n_embd": 768,
+  "n_head": 12,
+  "n_inner": null,
+  "n_layer": 12,
+  "n_positions": 1024,
+  "pad_token_id": null,
+  "reorder_and_upcast_attn": false,
+  "resid_pdrop": 0.1,
+  "scale_attn_by_inverse_layer_idx": false,
+  "scale_attn_weights": true,
+  "summary_activation": null,
+  "summary_first_dropout": 0.1,
+  "summary_proj_to_labels": true,
+  "summary_type": "cls_index",
+  "summary_use_proj": true,
+  "task_specific_params": {
+    "text-generation": {
+      "do_sample": true,
+      "max_length": 50
+    }
+  },
+  "tie_word_embeddings": true,
+  "transformers_version": "5.13.1",
+  "use_cache": true,
+  "vocab_size": 50257
+}

generation_config.json

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+{
+  "_from_model_config": true,
+  "bos_token_id": 50256,
+  "eos_token_id": 50256,
+  "transformers_version": "5.13.1"
+}

model.safetensors

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+oid sha256:c7d00560d8910fbed77ffad4065dee5011c41ba401b1064e749c498ba9e20373
+size 497774208

tokenizer_config.json

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+{
+  "add_prefix_space": false,
+  "backend": "tokenizers",
+  "bos_token": "<|endoftext|>",
+  "eos_token": "<|endoftext|>",
+  "errors": "replace",
+  "is_local": false,
+  "local_files_only": false,
+  "model_max_length": 1024,
+  "pad_token": null,
+  "tokenizer_class": "GPT2Tokenizer",
+  "unk_token": "<|endoftext|>"
+}